CSC 532 - Final Project
Read the file, get summary and structure
efw = read.csv("efw_cc.csv")
summary(efw) year ISO_code countries ECONOMIC.FREEDOM rank quartile
Min. :1970 AGO : 23 Albania : 23 Min. :1.970 Min. : 1.00 Min. :1.000
1st Qu.:1995 ALB : 23 Algeria : 23 1st Qu.:5.855 1st Qu.: 33.00 1st Qu.:1.000
Median :2005 ARE : 23 Angola : 23 Median :6.680 Median : 66.00 Median :3.000
Mean :2001 ARG : 23 Argentina: 23 Mean :6.520 Mean : 68.31 Mean :2.498
3rd Qu.:2011 ARM : 23 Armenia : 23 3rd Qu.:7.350 3rd Qu.:102.00 3rd Qu.:3.000
Max. :2016 AUS : 23 Australia: 23 Max. :9.190 Max. :162.00 Max. :4.000
(Other):3588 (Other) :3588 NA's :723 NA's :723 NA's :723
X1a_government_consumption X1b_transfers X1c_gov_enterprises X1d_top_marg_tax_rate X1_size_government
Min. : 0.000 Min. : 0.000 Min. : 0.000 Min. : 0.000 Min. :0.6538
1st Qu.: 4.450 1st Qu.: 6.208 1st Qu.: 4.000 1st Qu.: 4.000 1st Qu.:5.2294
Median : 6.082 Median : 8.432 Median : 7.000 Median : 6.000 Median :6.3197
Mean : 5.862 Mean : 7.673 Mean : 5.738 Mean : 5.813 Mean :6.2321
3rd Qu.: 7.571 3rd Qu.: 9.482 3rd Qu.: 8.000 3rd Qu.: 8.000 3rd Qu.:7.2677
Max. :10.000 Max. :10.000 Max. :10.000 Max. :10.000 Max. :9.9047
NA's :589 NA's :960 NA's :646 NA's :1047 NA's :647
X2a_judicial_independence X2b_impartial_courts X2c_protection_property_rights X2d_military_interference
Min. :0.000 Min. :0.000 Min. : 0.000 Min. : 0.000
1st Qu.:3.259 1st Qu.:3.352 1st Qu.: 4.093 1st Qu.: 4.500
Median :4.698 Median :4.333 Median : 5.299 Median : 6.667
Mean :5.019 Mean :4.675 Mean : 5.487 Mean : 6.510
3rd Qu.:6.823 3rd Qu.:5.857 3rd Qu.: 7.058 3rd Qu.: 8.333
Max. :9.817 Max. :9.686 Max. :10.000 Max. :10.000
NA's :1553 NA's :1179 NA's :1129 NA's :1186
X2e_integrity_legal_system X2f_legal_enforcement_contracts X2g_restrictions_sale_real_property
Min. : 0.000 Min. :0.000 Min. :0.000
1st Qu.: 4.167 1st Qu.:3.376 1st Qu.:6.001
Median : 6.667 Median :4.492 Median :7.528
Mean : 6.200 Mean :4.449 Mean :7.045
3rd Qu.: 8.333 3rd Qu.:5.583 3rd Qu.:8.523
Max. :10.000 Max. :8.479 Max. :9.981
NA's :1153 NA's :1361 NA's :1384
X2h_reliability_police X2i_business_costs_crime X2j_gender_adjustment X2_property_rights X3a_money_growth
Min. :0.000 Min. :0.000 Min. :0.0000 Min. :0.9556 Min. :0.000
1st Qu.:4.064 1st Qu.:4.641 1st Qu.:0.7931 1st Qu.:3.9439 1st Qu.:7.867
Median :5.321 Median :6.055 Median :0.9564 Median :5.2306 Median :8.697
Mean :5.505 Mean :5.904 Mean :0.8732 Mean :5.2529 Mean :8.235
3rd Qu.:7.111 3rd Qu.:7.315 3rd Qu.:1.0000 3rd Qu.:6.3925 3rd Qu.:9.256
Max. :9.688 Max. :9.673 Max. :1.0000 Max. :9.2783 Max. :9.999
NA's :2071 NA's :2071 NA's :66 NA's :755 NA's :644
X3b_std_inflation X3c_inflation X3d_freedom_own_foreign_currency X3_sound_money X4a_tariffs
Min. :0.000 Min. : 0.000 Min. : 0.00 Min. :0.000 Min. : 0.000
1st Qu.:7.555 1st Qu.: 8.192 1st Qu.: 0.00 1st Qu.:6.604 1st Qu.: 6.209
Median :8.881 Median : 9.106 Median : 5.00 Median :7.969 Median : 7.480
Mean :8.008 Mean : 8.464 Mean : 5.92 Mean :7.661 Mean : 7.079
3rd Qu.:9.404 3rd Qu.: 9.574 3rd Qu.:10.00 3rd Qu.:9.257 3rd Qu.: 8.334
Max. :9.952 Max. :10.000 Max. :10.00 Max. :9.922 Max. :10.000
NA's :607 NA's :607 NA's :621 NA's :611 NA's :681
X4b_regulatory_trade_barriers X4c_black_market X4d_control_movement_capital_ppl X4_trade
Min. :0.000 Min. : 0.000 Min. : 0.000 Min. : 0.000
1st Qu.:5.463 1st Qu.:10.000 1st Qu.: 2.000 1st Qu.: 5.947
Median :6.592 Median :10.000 Median : 4.769 Median : 7.011
Mean :6.333 Mean : 9.115 Mean : 4.376 Mean : 6.720
3rd Qu.:7.516 3rd Qu.:10.000 3rd Qu.: 6.493 3rd Qu.: 7.916
Max. :9.833 Max. :10.000 Max. :10.000 Max. :10.000
NA's :1348 NA's :617 NA's :592 NA's :691
X5a_credit_market_reg X5b_labor_market_reg X5c_business_reg X5_regulation
Min. : 0.000 Min. :1.837 Min. :2.010 Min. :1.002
1st Qu.: 6.800 1st Qu.:5.073 1st Qu.:5.387 1st Qu.:5.878
Median : 8.306 Median :6.197 Median :6.170 Median :6.759
Mean : 7.732 Mean :6.168 Mean :6.189 Mean :6.638
3rd Qu.: 9.333 3rd Qu.:7.344 3rd Qu.:7.007 3rd Qu.:7.486
Max. :10.000 Max. :9.725 Max. :9.504 Max. :9.440
NA's :619 NA's :1158 NA's :1402 NA's :728 str(efw)'data.frame': 3726 obs. of 36 variables:
$ year : int 2016 2016 2016 2016 2016 2016 2016 2016 2016 2016 ...
$ ISO_code : Factor w/ 162 levels "AGO","ALB","ARE",..: 2 43 1 4 5 6 7 8 16 15 ...
$ countries : Factor w/ 162 levels "Albania","Algeria",..: 1 2 3 4 5 6 7 8 9 10 ...
$ ECONOMIC.FREEDOM : num 7.54 4.99 5.17 4.84 7.57 7.98 7.58 6.49 7.34 7.56 ...
$ rank : int 34 159 155 160 29 10 27 106 49 30 ...
$ quartile : int 1 4 4 4 1 1 1 3 2 1 ...
$ X1a_government_consumption : num 8.23 2.15 7.6 5.34 7.26 ...
$ X1b_transfers : num 7.51 7.82 8.89 6.05 7.75 ...
$ X1c_gov_enterprises : int 8 0 0 6 8 10 10 0 7 10 ...
$ X1d_top_marg_tax_rate : num 8 4.5 9.5 4 5 5 3.5 6.5 10 10 ...
$ X1_size_government : num 7.94 3.62 6.5 5.35 7 ...
$ X2a_judicial_independence : num 2.67 4.19 1.84 3.69 3.87 ...
$ X2b_impartial_courts : num 3.15 4.33 1.97 2.93 4.2 ...
$ X2c_protection_property_rights : num 4.51 4.69 2.51 4.26 5.66 ...
$ X2d_military_interference : num 8.33 4.17 3.33 7.5 5.83 ...
$ X2e_integrity_legal_system : num 4.17 5 4.17 3.33 5 ...
$ X2f_legal_enforcement_contracts : num 4.39 4.51 2.3 3.63 5.2 ...
$ X2g_restrictions_sale_real_property: num 6.49 6.63 5.46 6.86 9.8 ...
$ X2h_reliability_police : num 6.93 6.14 3.02 3.39 5.71 ...
$ X2i_business_costs_crime : num 6.22 6.74 4.29 4.13 7.01 ...
$ X2j_gender_adjustment : num 0.949 0.821 0.846 0.769 1 ...
$ X2_property_rights : num 5.07 4.69 2.96 3.9 5.81 ...
$ X3a_money_growth : num 8.99 6.96 9.39 5.23 9.08 ...
$ X3b_std_inflation : num 9.48 8.34 4.99 5.22 9.26 ...
$ X3c_inflation : num 9.74 8.72 3.05 2 9.75 ...
$ X3d_freedom_own_foreign_currency : int 10 5 5 10 10 10 10 5 0 10 ...
$ X3_sound_money : num 9.55 7.25 5.61 5.61 9.52 ...
$ X4a_tariffs : num 8.96 6.87 6.99 6.42 8.55 ...
$ X4b_regulatory_trade_barriers : num 7.49 2.48 2.02 4.81 7.19 ...
$ X4c_black_market : num 10 5.56 10 0 10 ...
$ X4d_control_movement_capital_ppl : num 6.41 1.59 2.04 4.7 6.83 ...
$ X4_trade : num 8.21 4.13 5.26 3.98 8.14 ...
$ X5a_credit_market_reg : num 7.1 5.1 7.06 5.42 9.1 ...
$ X5b_labor_market_reg : num 6.92 5.03 4.56 5.15 6.23 ...
$ X5c_business_reg : num 6.71 5.68 4.93 5.54 6.8 ...
$ X5_regulation : num 6.91 5.27 5.52 5.37 7.38 ...Get variables that have more than 40% missing values
colMeans(is.na(efw)) year ISO_code countries
0.00000000 0.00000000 0.00000000
ECONOMIC.FREEDOM rank quartile
0.19404187 0.19404187 0.19404187
X1a_government_consumption X1b_transfers X1c_gov_enterprises
0.15807837 0.25764895 0.17337627
X1d_top_marg_tax_rate X1_size_government X2a_judicial_independence
0.28099839 0.17364466 0.41680086
X2b_impartial_courts X2c_protection_property_rights X2d_military_interference
0.31642512 0.30300590 0.31830381
X2e_integrity_legal_system X2f_legal_enforcement_contracts X2g_restrictions_sale_real_property
0.30944713 0.36527107 0.37144391
X2h_reliability_police X2i_business_costs_crime X2j_gender_adjustment
0.55582394 0.55582394 0.01771337
X2_property_rights X3a_money_growth X3b_std_inflation
0.20263017 0.17283951 0.16290929
X3c_inflation X3d_freedom_own_foreign_currency X3_sound_money
0.16290929 0.16666667 0.16398282
X4a_tariffs X4b_regulatory_trade_barriers X4c_black_market
0.18276973 0.36178207 0.16559313
X4d_control_movement_capital_ppl X4_trade X5a_credit_market_reg
0.15888352 0.18545357 0.16612990
X5b_labor_market_reg X5c_business_reg X5_regulation
0.31078905 0.37627483 0.19538379 which(colMeans(is.na(efw)) > 0.4)X2a_judicial_independence X2h_reliability_police X2i_business_costs_crime
12 19 20 Check that variables with more than 40% missing values aren’t correlated All three variables seem to be correlated since they have really low p values, so none of them will be removed.
library(gmodels)
X2a_judicial_independence <- ifelse(is.na(efw$X2a_judicial_independence), "Missing", "Observed")
CrossTable(X2a_judicial_independence, efw$ECONOMIC.FREEDOM, chisq = TRUE)
X2h_reliability_police <- ifelse(is.na(efw$X2h_reliability_police), "Missing", "Observed")
CrossTable(X2h_reliability_police, efw$ECONOMIC.FREEDOM, chisq = TRUE)
X2i_business_costs_crime <- ifelse(is.na(efw$X2i_business_costs_crime), "Missing", "Observed")
CrossTable(X2i_business_costs_crime, efw$ECONOMIC.FREEDOM, chisq = TRUE)Handle missing variables
ic <- efw$ISO_code
co <- efw$countries
efw <- efw[, !colnames(efw) %in% c("ISO_code","countries")]
for (i in 1:ncol(efw)) {
temp <- efw[, i]
temp[is.na(temp)] <- mean(temp, na.rm = TRUE)
efw[, i] <- temp
}
efw$ISO_code <- ic
efw$countries <- coHistogram The histogram is left-skewed, meaning that most countries in the world are considered to have good economic freedom.
hist(efw$ECONOMIC.FREEDOM)
Which variables seem to have the most correlation (plots, boxplots, cor function) Based on the below plots, most of the variables seem to have some correlation to a country’s economic freedom, with the exception of rank, quartile, X1a_government_consumption, and X1b_transfers.
plot(ECONOMIC.FREEDOM~., data=efw)
cor(efw[, !colnames(efw) %in% c("ISO_code","countries")]) year ECONOMIC.FREEDOM rank quartile
year 1.0000000000 0.2956699 0.199690169 -0.0007425666
ECONOMIC.FREEDOM 0.2956699277 1.0000000 -0.713155005 -0.8167402835
rank 0.1996901687 -0.7131550 1.000000000 0.9202482853
quartile -0.0007425666 -0.8167403 0.920248285 1.0000000000
X1a_government_consumption -0.0782265198 -0.2244959 0.217407984 0.2665670272
X1b_transfers -0.0290479381 -0.2672682 0.331765998 0.3549625307
X1c_gov_enterprises 0.2047313461 0.5441095 -0.426570214 -0.4807570398
X1d_top_marg_tax_rate 0.2556386657 0.2464800 0.004454262 -0.0588743983
X1_size_government 0.2154930133 0.2886722 -0.065058689 -0.1062103818
X2a_judicial_independence -0.0312576572 0.4151821 -0.542041290 -0.5030696520
X2b_impartial_courts -0.0773123828 0.4442758 -0.565987370 -0.5119352230
X2c_protection_property_rights 0.0210195666 0.5599062 -0.565533995 -0.5873082490
X2d_military_interference -0.0139540778 0.5223579 -0.627730277 -0.6036195319
X2e_integrity_legal_system 0.0148660390 0.5067464 -0.522403677 -0.5307676586
X2f_legal_enforcement_contracts -0.0088778458 0.3730324 -0.465337536 -0.4418969494
X2g_restrictions_sale_real_property 0.0558644462 0.3562865 -0.402095475 -0.4219739483
X2h_reliability_police 0.0038850819 0.3503402 -0.481048951 -0.4381831993
X2i_business_costs_crime -0.0080110906 0.2722793 -0.371449943 -0.3366046994
X2j_gender_adjustment 0.1416919776 0.3361467 -0.289863946 -0.3267685177
X2_property_rights 0.0421888631 0.7118521 -0.716081108 -0.7346309810
X3a_money_growth 0.1402450329 0.4617582 -0.270699712 -0.3309987333
X3b_std_inflation 0.1441767128 0.5248730 -0.354868613 -0.3999842028
X3c_inflation 0.2521926548 0.5408526 -0.254219625 -0.3350211883
X3d_freedom_own_foreign_currency 0.2377507885 0.6278666 -0.538000286 -0.6134385473
X3_sound_money 0.2895907903 0.8006828 -0.569369099 -0.6649230765
X4a_tariffs 0.2759294252 0.5889924 -0.364763637 -0.4691186450
X4b_regulatory_trade_barriers -0.0604212519 0.5105655 -0.662193559 -0.5946581846
X4c_black_market 0.3902707803 0.5214977 -0.168940987 -0.2720653839
X4d_control_movement_capital_ppl 0.3217321710 0.7216153 -0.543579667 -0.6317641872
X1a_government_consumption X1b_transfers X1c_gov_enterprises
year -0.07822652 -0.02904794 0.20473135
ECONOMIC.FREEDOM -0.22449586 -0.26726818 0.54410949
rank 0.21740798 0.33176600 -0.42657021
quartile 0.26656703 0.35496253 -0.48075704
X1a_government_consumption 1.00000000 0.44870355 -0.12640844
X1b_transfers 0.44870355 1.00000000 -0.30949119
X1c_gov_enterprises -0.12640844 -0.30949119 1.00000000
X1d_top_marg_tax_rate 0.14583741 0.33322637 -0.07665677
X1_size_government 0.55544032 0.51379050 0.42907662
X2a_judicial_independence -0.37965254 -0.33670257 0.19636513
X2b_impartial_courts -0.35725175 -0.24345626 0.17250607
X2c_protection_property_rights -0.33394183 -0.36652921 0.26892902
X2d_military_interference -0.44065743 -0.49036170 0.33324452
X2e_integrity_legal_system -0.44990218 -0.49531108 0.24556888
X2f_legal_enforcement_contracts -0.27412403 -0.35210208 0.21949240
X2g_restrictions_sale_real_property -0.19481969 -0.21847971 0.19273634
X2h_reliability_police -0.32093409 -0.28906755 0.17013410
X2i_business_costs_crime -0.29096176 -0.28791488 0.12118977
X2j_gender_adjustment -0.10456040 -0.26933914 0.25644646
X2_property_rights -0.44463610 -0.53051268 0.36627723
X3a_money_growth -0.12674657 -0.09232827 0.13381810
X3b_std_inflation -0.03230468 -0.19942685 0.27165632
X3c_inflation -0.20199252 -0.13493175 0.19645708
X3d_freedom_own_foreign_currency -0.23039318 -0.29184425 0.32584292
X3_sound_money -0.23389750 -0.29457170 0.36722792
X4a_tariffs -0.26150152 -0.31416844 0.34203641
X4b_regulatory_trade_barriers -0.28485814 -0.41660472 0.29832177
X4c_black_market -0.12220313 -0.03821086 0.25778001
X4d_control_movement_capital_ppl -0.20840815 -0.29174156 0.39393346
X1d_top_marg_tax_rate X1_size_government X2a_judicial_independence
year 0.255638666 0.215493013 -0.03125766
ECONOMIC.FREEDOM 0.246480010 0.288672171 0.41518210
rank 0.004454262 -0.065058689 -0.54204129
quartile -0.058874398 -0.106210382 -0.50306965
X1a_government_consumption 0.145837412 0.555440316 -0.37965254
X1b_transfers 0.333226369 0.513790496 -0.33670257
X1c_gov_enterprises -0.076656771 0.429076621 0.19636513
X1d_top_marg_tax_rate 1.000000000 0.563456693 -0.15145315
X1_size_government 0.563456693 1.000000000 -0.22140062
X2a_judicial_independence -0.151453146 -0.221400617 1.00000000
X2b_impartial_courts -0.096143498 -0.163615313 0.85156193
X2c_protection_property_rights -0.147345210 -0.155537310 0.71711530
X2d_military_interference -0.095504301 -0.196805359 0.53866424
X2e_integrity_legal_system -0.139751399 -0.259251532 0.53345340
X2f_legal_enforcement_contracts -0.015218804 -0.113815138 0.33093893
X2g_restrictions_sale_real_property 0.125144900 0.009007285 0.15759624
X2h_reliability_police -0.116152439 -0.176839552 0.68594428
X2i_business_costs_crime -0.060617663 -0.170844663 0.46847617
X2j_gender_adjustment -0.065596871 0.017664774 0.09884896
X2_property_rights -0.104185580 -0.178116985 0.66832642
X3a_money_growth 0.056080452 0.026492291 0.17829694
X3b_std_inflation -0.032478433 0.076134348 0.18273747
X3c_inflation 0.088507878 0.029937097 0.19269972
X3d_freedom_own_foreign_currency 0.219847852 0.114821297 0.21639564
X3_sound_money 0.160810347 0.109047563 0.28217403
X4a_tariffs 0.115242712 0.049685597 0.11933682
X4b_regulatory_trade_barriers -0.080987342 -0.128973700 0.55226815
X4c_black_market 0.168707951 0.186780432 0.08628143
X4d_control_movement_capital_ppl 0.146235997 0.140169843 0.25271433
X2b_impartial_courts X2c_protection_property_rights
year -0.07731238 0.02101957
ECONOMIC.FREEDOM 0.44427582 0.55990616
rank -0.56598737 -0.56553400
quartile -0.51193522 -0.58730825
X1a_government_consumption -0.35725175 -0.33394183
X1b_transfers -0.24345626 -0.36652921
X1c_gov_enterprises 0.17250607 0.26892902
X1d_top_marg_tax_rate -0.09614350 -0.14734521
X1_size_government -0.16361531 -0.15553731
X2a_judicial_independence 0.85156193 0.71711530
X2b_impartial_courts 1.00000000 0.64885079
X2c_protection_property_rights 0.64885079 1.00000000
X2d_military_interference 0.54551687 0.43190036
X2e_integrity_legal_system 0.54435350 0.59272467
X2f_legal_enforcement_contracts 0.39177491 0.31203852
X2g_restrictions_sale_real_property 0.19321683 0.17584376
X2h_reliability_police 0.58717569 0.57443761
X2i_business_costs_crime 0.42002320 0.42084520
X2j_gender_adjustment 0.09695814 0.14594679
X2_property_rights 0.70004836 0.76215642
X3a_money_growth 0.18517914 0.27989924
X3b_std_inflation 0.18731718 0.29285674
X3c_inflation 0.19378954 0.28616762
X3d_freedom_own_foreign_currency 0.17809980 0.26876474
X3_sound_money 0.26296865 0.39839838
X4a_tariffs 0.11469393 0.29315050
X4b_regulatory_trade_barriers 0.55280108 0.47921150
X4c_black_market 0.10183090 0.22433177
X4d_control_movement_capital_ppl 0.26527778 0.33841635
X2d_military_interference X2e_integrity_legal_system
year -0.01395408 0.01486604
ECONOMIC.FREEDOM 0.52235787 0.50674637
rank -0.62773028 -0.52240368
quartile -0.60361953 -0.53076766
X1a_government_consumption -0.44065743 -0.44990218
X1b_transfers -0.49036170 -0.49531108
X1c_gov_enterprises 0.33324452 0.24556888
X1d_top_marg_tax_rate -0.09550430 -0.13975140
X1_size_government -0.19680536 -0.25925153
X2a_judicial_independence 0.53866424 0.53345340
X2b_impartial_courts 0.54551687 0.54435350
X2c_protection_property_rights 0.43190036 0.59272467
X2d_military_interference 1.00000000 0.53128087
X2e_integrity_legal_system 0.53128087 1.00000000
X2f_legal_enforcement_contracts 0.43916273 0.45810543
X2g_restrictions_sale_real_property 0.35942161 0.25792373
X2h_reliability_police 0.42537323 0.48233268
X2i_business_costs_crime 0.33774725 0.48190120
X2j_gender_adjustment 0.25527436 0.19051524
X2_property_rights 0.72086492 0.78685389
X3a_money_growth 0.18641108 0.21169275
X3b_std_inflation 0.26073831 0.23918230
X3c_inflation 0.19455938 0.23954289
X3d_freedom_own_foreign_currency 0.36221604 0.28237983
X3_sound_money 0.39662142 0.36031450
X4a_tariffs 0.22253180 0.26733727
X4b_regulatory_trade_barriers 0.56899787 0.46138962
X4c_black_market 0.13312652 0.18735380
X4d_control_movement_capital_ppl 0.39307606 0.34188694
X2f_legal_enforcement_contracts X2g_restrictions_sale_real_property
year -0.008877846 0.055864446
ECONOMIC.FREEDOM 0.373032350 0.356286543
rank -0.465337536 -0.402095475
quartile -0.441896949 -0.421973948
X1a_government_consumption -0.274124028 -0.194819695
X1b_transfers -0.352102078 -0.218479713
X1c_gov_enterprises 0.219492404 0.192736343
X1d_top_marg_tax_rate -0.015218804 0.125144900
X1_size_government -0.113815138 0.009007285
X2a_judicial_independence 0.330938928 0.157596237
X2b_impartial_courts 0.391774908 0.193216832
X2c_protection_property_rights 0.312038522 0.175843762
X2d_military_interference 0.439162729 0.359421606
X2e_integrity_legal_system 0.458105427 0.257923730
X2f_legal_enforcement_contracts 1.000000000 0.498470981
X2g_restrictions_sale_real_property 0.498470981 1.000000000
X2h_reliability_police 0.340564138 0.168658085
X2i_business_costs_crime 0.372349425 0.166111214
X2j_gender_adjustment 0.223528614 0.157021763
X2_property_rights 0.585653277 0.439064201
X3a_money_growth 0.047908583 0.046917073
X3b_std_inflation 0.092878428 0.066061769
X3c_inflation 0.082967382 0.064501025
X3d_freedom_own_foreign_currency 0.292134167 0.327955520
X3_sound_money 0.237451963 0.247384419
X4a_tariffs 0.189623567 0.221194495
X4b_regulatory_trade_barriers 0.411894377 0.280888249
X4c_black_market 0.024707420 0.031797833
X4d_control_movement_capital_ppl 0.244819731 0.283151129
X2h_reliability_police X2i_business_costs_crime X2j_gender_adjustment
year 0.003885082 -0.008011091 0.141691978
ECONOMIC.FREEDOM 0.350340166 0.272279281 0.336146677
rank -0.481048951 -0.371449943 -0.289863946
quartile -0.438183199 -0.336604699 -0.326768518
X1a_government_consumption -0.320934085 -0.290961760 -0.104560396
X1b_transfers -0.289067546 -0.287914879 -0.269339136
X1c_gov_enterprises 0.170134098 0.121189768 0.256446461
X1d_top_marg_tax_rate -0.116152439 -0.060617663 -0.065596871
X1_size_government -0.176839552 -0.170844663 0.017664774
X2a_judicial_independence 0.685944284 0.468476167 0.098848959
X2b_impartial_courts 0.587175685 0.420023203 0.096958143
X2c_protection_property_rights 0.574437613 0.420845199 0.145946788
X2d_military_interference 0.425373235 0.337747247 0.255274356
X2e_integrity_legal_system 0.482332680 0.481901198 0.190515242
X2f_legal_enforcement_contracts 0.340564138 0.372349425 0.223528614
X2g_restrictions_sale_real_property 0.168658085 0.166111214 0.157021763
X2h_reliability_police 1.000000000 0.768006216 0.032362458
X2i_business_costs_crime 0.768006216 1.000000000 0.002526734
X2j_gender_adjustment 0.032362458 0.002526734 1.000000000
X2_property_rights 0.547526004 0.464169164 0.423002940
X3a_money_growth 0.139951072 0.094562572 0.017282136
X3b_std_inflation 0.127659260 0.055907278 0.198014724
X3c_inflation 0.174109861 0.146007674 0.061742936
X3d_freedom_own_foreign_currency 0.197425244 0.163165373 0.220250218
X3_sound_money 0.239201879 0.178015591 0.218690803
X4a_tariffs 0.107007026 0.102351041 0.224120794
X4b_regulatory_trade_barriers 0.464800857 0.378869726 0.204918170
X4c_black_market 0.072257214 0.074336665 0.081283062
X4d_control_movement_capital_ppl 0.183188071 0.098106449 0.348301438
X2_property_rights X3a_money_growth X3b_std_inflation X3c_inflation
year 0.04218886 0.14024503 0.14417671 0.25219265
ECONOMIC.FREEDOM 0.71185205 0.46175819 0.52487299 0.54085263
rank -0.71608111 -0.27069971 -0.35486861 -0.25421962
quartile -0.73463098 -0.33099873 -0.39998420 -0.33502119
X1a_government_consumption -0.44463610 -0.12674657 -0.03230468 -0.20199252
X1b_transfers -0.53051268 -0.09232827 -0.19942685 -0.13493175
X1c_gov_enterprises 0.36627723 0.13381810 0.27165632 0.19645708
X1d_top_marg_tax_rate -0.10418558 0.05608045 -0.03247843 0.08850788
X1_size_government -0.17811698 0.02649229 0.07613435 0.02993710
X2a_judicial_independence 0.66832642 0.17829694 0.18273747 0.19269972
X2b_impartial_courts 0.70004836 0.18517914 0.18731718 0.19378954
X2c_protection_property_rights 0.76215642 0.27989924 0.29285674 0.28616762
X2d_military_interference 0.72086492 0.18641108 0.26073831 0.19455938
X2e_integrity_legal_system 0.78685389 0.21169275 0.23918230 0.23954289
X2f_legal_enforcement_contracts 0.58565328 0.04790858 0.09287843 0.08296738
X2g_restrictions_sale_real_property 0.43906420 0.04691707 0.06606177 0.06450103
X2h_reliability_police 0.54752600 0.13995107 0.12765926 0.17410986
X2i_business_costs_crime 0.46416916 0.09456257 0.05590728 0.14600767
X2j_gender_adjustment 0.42300294 0.01728214 0.19801472 0.06174294
X2_property_rights 1.00000000 0.23978827 0.32651501 0.27594406
X3a_money_growth 0.23978827 1.00000000 0.60376306 0.60915888
X3b_std_inflation 0.32651501 0.60376306 1.00000000 0.56840260
X3c_inflation 0.27594406 0.60915888 0.56840260 1.00000000
X3d_freedom_own_foreign_currency 0.39957147 0.10518109 0.14051510 0.14905840
X3_sound_money 0.47554055 0.65050684 0.68847577 0.68601793
X4a_tariffs 0.37541174 0.19107265 0.20441680 0.27522449
X4b_regulatory_trade_barriers 0.60011334 0.18908418 0.25967825 0.22472129
X4c_black_market 0.24354329 0.25981557 0.26261929 0.41187737
X4d_control_movement_capital_ppl 0.50846418 0.17524709 0.29061029 0.26335324
X3d_freedom_own_foreign_currency X3_sound_money X4a_tariffs
year 0.2377508 0.2895908 0.27592943
ECONOMIC.FREEDOM 0.6278666 0.8006828 0.58899240
rank -0.5380003 -0.5693691 -0.36476364
quartile -0.6134385 -0.6649231 -0.46911864
X1a_government_consumption -0.2303932 -0.2338975 -0.26150152
X1b_transfers -0.2918442 -0.2945717 -0.31416844
X1c_gov_enterprises 0.3258429 0.3672279 0.34203641
X1d_top_marg_tax_rate 0.2198479 0.1608103 0.11524271
X1_size_government 0.1148213 0.1090476 0.04968560
X2a_judicial_independence 0.2163956 0.2821740 0.11933682
X2b_impartial_courts 0.1780998 0.2629687 0.11469393
X2c_protection_property_rights 0.2687647 0.3983984 0.29315050
X2d_military_interference 0.3622160 0.3966214 0.22253180
X2e_integrity_legal_system 0.2823798 0.3603145 0.26733727
X2f_legal_enforcement_contracts 0.2921342 0.2374520 0.18962357
X2g_restrictions_sale_real_property 0.3279555 0.2473844 0.22119450
X2h_reliability_police 0.1974252 0.2392019 0.10700703
X2i_business_costs_crime 0.1631654 0.1780156 0.10235104
X2j_gender_adjustment 0.2202502 0.2186908 0.22412079
X2_property_rights 0.3995715 0.4755405 0.37541174
X3a_money_growth 0.1051811 0.6505068 0.19107265
X3b_std_inflation 0.1405151 0.6884758 0.20441680
X3c_inflation 0.1490584 0.6860179 0.27522449
X3d_freedom_own_foreign_currency 1.0000000 0.7166894 0.48352447
X3_sound_money 0.7166894 1.0000000 0.47573779
X4a_tariffs 0.4835245 0.4757378 1.00000000
X4b_regulatory_trade_barriers 0.3247972 0.3841048 0.25590708
X4c_black_market 0.2766225 0.4252340 0.38263583
X4d_control_movement_capital_ppl 0.6492453 0.5969797 0.50996079
X4b_regulatory_trade_barriers X4c_black_market
year -0.06042125 0.39027078
ECONOMIC.FREEDOM 0.51056554 0.52149768
rank -0.66219356 -0.16894099
quartile -0.59465818 -0.27206538
X1a_government_consumption -0.28485814 -0.12220313
X1b_transfers -0.41660472 -0.03821086
X1c_gov_enterprises 0.29832177 0.25778001
X1d_top_marg_tax_rate -0.08098734 0.16870795
X1_size_government -0.12897370 0.18678043
X2a_judicial_independence 0.55226815 0.08628143
X2b_impartial_courts 0.55280108 0.10183090
X2c_protection_property_rights 0.47921150 0.22433177
X2d_military_interference 0.56899787 0.13312652
X2e_integrity_legal_system 0.46138962 0.18735380
X2f_legal_enforcement_contracts 0.41189438 0.02470742
X2g_restrictions_sale_real_property 0.28088825 0.03179783
X2h_reliability_police 0.46480086 0.07225721
X2i_business_costs_crime 0.37886973 0.07433666
X2j_gender_adjustment 0.20491817 0.08128306
X2_property_rights 0.60011334 0.24354329
X3a_money_growth 0.18908418 0.25981557
X3b_std_inflation 0.25967825 0.26261929
X3c_inflation 0.22472129 0.41187737
X3d_freedom_own_foreign_currency 0.32479724 0.27662253
X3_sound_money 0.38410480 0.42523402
X4a_tariffs 0.25590708 0.38263583
X4b_regulatory_trade_barriers 1.00000000 0.09463075
X4c_black_market 0.09463075 1.00000000
X4d_control_movement_capital_ppl 0.37592229 0.39830466
X4d_control_movement_capital_ppl X4_trade X5a_credit_market_reg
year 0.32173217 0.3137235 0.3801761
ECONOMIC.FREEDOM 0.72161529 0.8344904 0.6479169
rank -0.54357967 -0.5523520 -0.3628255
quartile -0.63176419 -0.6602030 -0.4611504
X1a_government_consumption -0.20840815 -0.2848623 -0.2029750
X1b_transfers -0.29174156 -0.3382224 -0.1434629
X1c_gov_enterprises 0.39393346 0.4297962 0.3723975
X1d_top_marg_tax_rate 0.14623600 0.1452978 0.1607996
X1_size_government 0.14016984 0.1061270 0.1936774
X2a_judicial_independence 0.25271433 0.2856745 0.1522535
X2b_impartial_courts 0.26527778 0.2995718 0.1932551
X2c_protection_property_rights 0.33841635 0.4402531 0.2748088
X2d_military_interference 0.39307606 0.4005894 0.2793472
X2e_integrity_legal_system 0.34188694 0.4116469 0.2579037
X2f_legal_enforcement_contracts 0.24481973 0.2530979 0.1950625
X2g_restrictions_sale_real_property 0.28315113 0.2504225 0.1753448
X2h_reliability_police 0.18318807 0.2312669 0.1422842
X2i_business_costs_crime 0.09810645 0.1781775 0.1036015
X2j_gender_adjustment 0.34830144 0.2933960 0.2208672
X2_property_rights 0.50846418 0.5655722 0.3683319
X3a_money_growth 0.17524709 0.2877370 0.3133794
X3b_std_inflation 0.29061029 0.3570709 0.3929270
X3c_inflation 0.26335324 0.4215810 0.4304156
X3d_freedom_own_foreign_currency 0.64924528 0.5839543 0.3732176
X3_sound_money 0.59697966 0.6488338 0.5408772
X4a_tariffs 0.50996079 0.7643919 0.4497592
X4b_regulatory_trade_barriers 0.37592229 0.4724005 0.2413244
X4c_black_market 0.39830466 0.6626004 0.5295996
X4d_control_movement_capital_ppl 1.00000000 0.7940911 0.5431056
X5b_labor_market_reg X5c_business_reg X5_regulation
year 0.13272345 0.034844226 0.3238551
ECONOMIC.FREEDOM 0.33142034 0.530369628 0.7757552
rank -0.27071704 -0.620826715 -0.5191938
quartile -0.26817755 -0.588830603 -0.5976500
X1a_government_consumption -0.08656420 -0.287608246 -0.2702386
X1b_transfers 0.09028394 -0.246213734 -0.1325013
X1c_gov_enterprises 0.10277578 0.258669056 0.3734816
X1d_top_marg_tax_rate 0.19089283 -0.002762008 0.2111931
X1_size_government 0.14525665 -0.049952018 0.1821752
X2a_judicial_independence 0.24699200 0.667679781 0.3821897
X2b_impartial_courts 0.24078869 0.658320564 0.4075101
X2c_protection_property_rights 0.18418263 0.600787364 0.4352287
X2d_military_interference 0.26379264 0.501397992 0.4328235
X2e_integrity_legal_system 0.13866726 0.477079343 0.3832188
X2f_legal_enforcement_contracts 0.14729157 0.440745041 0.3038255
X2g_restrictions_sale_real_property 0.14153369 0.373219924 0.2754394
X2h_reliability_police 0.22963117 0.589646111 0.3461619
X2i_business_costs_crime 0.18274446 0.457127361 0.2663228
X2j_gender_adjustment 0.05123183 0.124902168 0.2190698
X2_property_rights 0.21709190 0.612083579 0.5268150
X3a_money_growth 0.13285559 0.220516473 0.3569457
X3b_std_inflation 0.04086118 0.219380869 0.3563961
X3c_inflation 0.13255307 0.240225555 0.4407290
X3d_freedom_own_foreign_currency 0.13421443 0.289844884 0.3876354
X3_sound_money 0.16239288 0.361563775 0.5522046
X4a_tariffs 0.01906554 0.196690790 0.3859626
X4b_regulatory_trade_barriers 0.18095694 0.608942357 0.3894993
X4c_black_market 0.09147938 0.112868433 0.4246290
X4d_control_movement_capital_ppl 0.16427184 0.297050432 0.5181823
[ reached getOption("max.print") -- omitted 5 rows ]Split between train and test data (90% train, 10% test)
library(caret)
set.seed(1)
inTrain = createDataPartition(efw$ECONOMIC.FREEDOM, p=0.9, list=FALSE)
efw_train <- efw[inTrain, ]
trainLabel <- efw[inTrain, 2]
efw_test <- efw[-inTrain, ]
testLabel <- efw[-inTrain, 2]Lasso Linear Regression RMSE = 0.2470609
set.seed(1)
lasso <- train(ECONOMIC.FREEDOM~., data=efw_train, method="glmnet", trControl=trainControl("cv", number=10), tuneGrid=expand.grid(alpha=1, lambda=10^seq(-3, 3, length=100)))There were missing values in resampled performance measures.coef(lasso$finalModel, lasso$bestTune$lambda)356 x 1 sparse Matrix of class "dgCMatrix"
1
(Intercept) 1.552131e+00
year -4.038343e-04
rank 8.743194e-04
quartile -1.113946e-01
X1a_government_consumption 9.917899e-04
X1b_transfers .
X1c_gov_enterprises 1.436746e-03
X1d_top_marg_tax_rate 4.591901e-03
X1_size_government 1.723889e-01
X2a_judicial_independence -4.886966e-03
X2b_impartial_courts .
X2c_protection_property_rights -1.087821e-03
X2d_military_interference 1.785583e-03
X2e_integrity_legal_system -3.818862e-04
X2f_legal_enforcement_contracts -7.677424e-03
X2g_restrictions_sale_real_property -3.867844e-04
X2h_reliability_police .
X2i_business_costs_crime .
X2j_gender_adjustment -3.175529e-02
X2_property_rights 1.903367e-01
X3a_money_growth 4.658241e-02
X3b_std_inflation 3.762006e-02
X3c_inflation 5.543481e-02
X3d_freedom_own_foreign_currency 3.859770e-02
X3_sound_money 9.347317e-03
X4a_tariffs -1.067940e-02
X4b_regulatory_trade_barriers -1.418735e-02
X4c_black_market -2.506671e-02
X4d_control_movement_capital_ppl -1.665939e-02
X4_trade 2.535080e-01
X5a_credit_market_reg -2.063522e-02
X5b_labor_market_reg -1.179711e-02
X5c_business_reg -7.195245e-03
X5_regulation 2.329467e-01
ISO_codeALB -5.007477e-02
ISO_codeARE .
ISO_codeARG 1.932016e-02
ISO_codeARM .
ISO_codeAUS .
ISO_codeAUT -1.673076e-02
ISO_codeAZE 5.987736e-03
ISO_codeBDI .
ISO_codeBEL -2.514225e-02
ISO_codeBEN -1.357529e-02
ISO_codeBFA .
ISO_codeBGD -2.010186e-02
ISO_codeBGR -3.943447e-02
ISO_codeBHR -1.029912e-03
ISO_codeBHS .
ISO_codeBIH .
ISO_codeBLR .
ISO_codeBLZ .
ISO_codeBOL 7.694005e-02
ISO_codeBRA 1.900567e-02
ISO_codeBRD -1.893823e-02
ISO_codeBRN -3.584972e-03
ISO_codeBTN .
ISO_codeBWA .
ISO_codeCAF -1.186013e-02
ISO_codeCAN -1.098076e-02
ISO_codeCHE 1.827803e-03
ISO_codeCHL -1.654339e-02
ISO_codeCHN 1.816832e-02
ISO_codeCIV 4.568518e-02
ISO_codeCMR 4.890389e-02
ISO_codeCOD -8.963729e-05
ISO_codeCOG -3.617592e-02
ISO_codeCOL .
ISO_codeCPV 7.056602e-05
ISO_codeCRI -3.630306e-02
ISO_codeCYP -1.197519e-02
ISO_codeCZE -5.836778e-02
ISO_codeDEU -3.634660e-02
ISO_codeDNK -4.250495e-02
ISO_codeDOM 8.114538e-02
ISO_codeDZA -3.529663e-02
ISO_codeECU 3.458086e-02
ISO_codeEGY 8.088507e-02
ISO_codeESP -2.098773e-02
ISO_codeEST 1.124039e-03
ISO_codeETH 3.523364e-03
ISO_codeFIN -2.509817e-02
ISO_codeFJI .
ISO_codeFRA -9.547603e-03
ISO_codeGAB 7.271861e-02
ISO_codeGBR -1.774344e-02
ISO_codeGEO .
ISO_codeGHA 1.127589e-01
ISO_codeGIN 2.205910e-02
ISO_codeGMB .
ISO_codeGNB 4.618337e-02
ISO_codeGRC .
ISO_codeGTM 3.136058e-02
ISO_codeGUY 1.330253e-01
ISO_codeHKG 4.353908e-02
ISO_codeHND -1.880945e-02
ISO_codeHRV 4.114010e-03
ISO_codeHTI .
ISO_codeHUN .
ISO_codeIDN 5.533674e-03
ISO_codeIND -1.412311e-02
ISO_codeIRL -3.349971e-02
ISO_codeIRN .
ISO_codeIRQ 2.171219e-02
ISO_codeISL -1.021749e-02
ISO_codeISR .
ISO_codeITA -3.474211e-02
ISO_codeJAM 5.301807e-02
ISO_codeJOR -6.980283e-03
ISO_codeJPN -3.925629e-02
ISO_codeKAZ .
ISO_codeKEN .
ISO_codeKGZ 2.290686e-02
ISO_codeKHM .
ISO_codeKOR .
ISO_codeKWT -5.505598e-02
ISO_codeLAO 1.281845e-03
ISO_codeLBN .
ISO_codeLBR 7.815495e-05
ISO_codeLBY 1.708764e-02
ISO_codeLKA 1.209251e-01
ISO_codeLSO 1.544122e-02
ISO_codeLTU -3.169371e-02
ISO_codeLUX -1.271197e-02
ISO_codeLVA -1.265204e-02
ISO_codeMAR -2.712615e-02
ISO_codeMDA 1.387123e-02
ISO_codeMDG 1.053703e-01
ISO_codeMEX 4.037941e-02
ISO_codeMKD -4.078710e-03
ISO_codeMLI .
ISO_codeMLT -1.214105e-02
ISO_codeMMR -3.353754e-02
ISO_codeMNE .
ISO_codeMNG 1.489087e-04
ISO_codeMOZ 1.404227e-01
ISO_codeMRT 1.594300e-03
ISO_codeMUS .
ISO_codeMWI 3.051857e-02
ISO_codeMYS -3.093028e-02
ISO_codeNAM 9.640121e-02
ISO_codeNER .
ISO_codeNGA .
ISO_codeNIC -2.552056e-02
ISO_codeNLD -5.018456e-02
ISO_codeNOR -3.479804e-02
ISO_codeNPL 7.132260e-02
ISO_codeNZL -1.712067e-04
ISO_codeOMN .
ISO_codePAK 2.985968e-02
ISO_codePAN -5.727453e-02
ISO_codePER -4.002957e-02
ISO_codePHL .
ISO_codePNG 1.630848e-02
ISO_codePOL .
ISO_codePRT -2.532128e-02
ISO_codePRY .
ISO_codeQAT -1.991038e-02
ISO_codeROU 2.804415e-02
ISO_codeRUS 3.035556e-01
ISO_codeRWA .
ISO_codeSAU -1.684078e-03
ISO_codeSDN .
ISO_codeSEN 9.285805e-02
ISO_codeSGP 2.730275e-03
ISO_codeSLE 1.114790e-02
ISO_codeSLV .
ISO_codeSRB .
ISO_codeSUR 2.138995e-03
ISO_codeSVK -3.844658e-02
ISO_codeSVN -2.364258e-02
ISO_codeSWE -6.468094e-02
ISO_codeSWZ .
ISO_codeSYC .
ISO_codeSYR .
ISO_codeTCD -2.196641e-02
ISO_codeTGO 6.731609e-02
ISO_codeTHA 1.752897e-02
ISO_codeTJK 2.506273e-02
ISO_codeTLS 9.142515e-04
ISO_codeTTO -2.318531e-02
ISO_codeTUN -9.161736e-04
ISO_codeTUR 4.691630e-02
ISO_codeTWN -1.085651e-02
ISO_codeTZA .
ISO_codeUGA 9.437248e-03
ISO_codeUKR -6.792430e-02
ISO_codeURY 1.506797e-02
ISO_codeUSA .
ISO_codeVEN -6.463517e-02
ISO_codeVNM 7.615732e-03
ISO_codeYEM 4.133426e-03
ISO_codeZAF .
ISO_codeZMB .
ISO_codeZWE -1.884024e-02
countriesAlgeria -6.381438e-03
countriesAngola -1.027426e-02
countriesArgentina .
countriesArmenia .
countriesAustralia .
countriesAustria -1.610710e-03
countriesAzerbaijan .
countriesBahamas .
countriesBahrain -1.592996e-03
countriesBangladesh -4.029602e-03
countriesBarbados -3.577568e-03
countriesBelarus .
countriesBelgium -1.161696e-02
countriesBelize .
countriesBenin -2.437514e-03
countriesBhutan .
countriesBolivia .
countriesBosnia and Herzegovina .
countriesBotswana .
countriesBrazil .
countriesBrunei Darussalam -1.015189e-03
countriesBulgaria -3.898075e-03
countriesBurkina Faso .
countriesBurundi .
countriesCambodia .
countriesCameroon .
countriesCanada -1.394572e-03
countriesCape Verde .
countriesCentral Afr. Rep. -2.184391e-03
countriesChad -7.714739e-04
countriesChile -3.684775e-03
countriesChina .
countriesColombia .
countriesCongo, Dem. R. -3.223113e-05
countriesCongo, Rep. Of -3.453391e-03
countriesCosta Rica -3.762237e-03
countriesCote d'Ivoire .
countriesCroatia .
countriesCyprus -1.739958e-03
countriesCzech Rep. -2.194432e-03
countriesDenmark -3.065649e-03
countriesDominican Rep. .
countriesEcuador .
countriesEgypt .
countriesEl Salvador .
countriesEstonia .
countriesEthiopia .
countriesFiji .
countriesFinland -1.966901e-03
countriesFrance -1.238540e-03
countriesGabon .
countriesGambia, The .
countriesGeorgia .
countriesGermany -1.980659e-03
countriesGhana .
countriesGreece .
countriesGuatemala 1.017437e-03
countriesGuinea .
countriesGuinea-Bissau .
countriesGuyana .
countriesHaiti .
countriesHonduras -1.748357e-03
countriesHong Kong .
countriesHungary .
countriesIceland -1.160366e-03
countriesIndia -1.512781e-03
countriesIndonesia .
countriesIran .
countriesIraq .
countriesIreland -2.363283e-03
countriesIsrael .
countriesItaly -1.139187e-03
countriesJamaica .
countriesJapan -5.727358e-04
countriesJordan -9.167214e-04
countriesKazakhstan .
countriesKenya .
countriesKorea, South .
countriesKuwait -2.169874e-03
countriesKyrgyz Republic .
countriesLaos .
countriesLatvia -1.019378e-03
countriesLebanon .
countriesLesotho .
countriesLiberia .
countriesLibya .
countriesLithuania -5.479577e-04
countriesLuxembourg -8.542522e-04
countriesMacedonia -8.063178e-04
countriesMadagascar .
countriesMalawi .
countriesMalaysia -2.422088e-03
countriesMali .
countriesMalta -7.448210e-04
countriesMauritania .
countriesMauritius .
countriesMexico .
countriesMoldova .
countriesMongolia .
countriesMontenegro .
countriesMorocco -2.411531e-03
countriesMozambique .
countriesMyanmar -1.267295e-05
countriesNamibia .
countriesNepal .
countriesNetherlands -3.418678e-04
countriesNew Zealand -6.645560e-06
countriesNicaragua -1.880729e-03
countriesNiger .
countriesNigeria .
countriesNorway -1.286419e-03
countriesOman .
countriesPakistan .
countriesPanama -1.895569e-03
countriesPap. New Guinea .
countriesParaguay .
countriesPeru -2.319785e-03
countriesPhilippines .
countriesPoland .
countriesPortugal -1.244559e-03
countriesQatar -1.132620e-03
countriesRomania 9.220041e-03
countriesRussia .
countriesRwanda .
countriesSaudi Arabia -9.705055e-05
countriesSenegal .
countriesSerbia .
countriesSeychelles .
countriesSierra Leone .
countriesSingapore .
countriesSlovak Rep -5.175074e-05
countriesSlovenia -3.941559e-04
countriesSouth Africa .
countriesSpain -2.373901e-03
countriesSri Lanka .
countriesSudan .
countriesSuriname .
countriesSwaziland .
countriesSweden -4.937529e-04
countriesSwitzerland .
countriesSyria .
countriesTaiwan -9.235636e-04
countriesTajikistan .
countriesTanzania .
countriesThailand .
countriesTimor-Leste .
countriesTogo .
countriesTrinidad & Tob. -1.410374e-03
countriesTunisia -5.872716e-04
countriesTurkey .
countriesUganda .
countriesUkraine -1.214432e-03
countriesUnit. Arab Em. -8.489068e-02
countriesUnited Kingdom -1.931147e-03
countriesUnited States .
countriesUruguay .
countriesVenezuela -7.304584e-04
countriesVietnam .
countriesYemen, Rep. .
countriesZambia .
countriesZimbabwe -5.175861e-04predictions <- predict(lasso, efw_test)
RMSE(predictions, efw_test$ECONOMIC.FREEDOM)[1] 0.2470609Ridge Linear Regression Model RMSE = 0.2685492
set.seed(1)
ridge <- train(ECONOMIC.FREEDOM~., data=efw_train, method="glmnet", trControl=trainControl("cv", number=10), tuneGrid=expand.grid(alpha=0, lambda=10^seq(-3, 3, length=100)))There were missing values in resampled performance measures.predictions <- predict(ridge, efw_test)
RMSE(predictions, efw_test$ECONOMIC.FREEDOM)[1] 0.2685492Random forest RMSE = 0.2097298
grid <- expand.grid(mtry=c(2, 4, 8, 16))
set.seed(1)
rfModel <- train(ECONOMIC.FREEDOM~., data=efw_train, method="rf", trControl=trainControl(method="cv", number=10), tuneGrid=grid, importance=T)
rfModelRandom Forest
3355 samples
35 predictor
No pre-processing
Resampling: Cross-Validated (10 fold)
Summary of sample sizes: 3020, 3018, 3020, 3019, 3019, 3020, ...
Resampling results across tuning parameters:
mtry RMSE Rsquared MAE
2 0.5278366 0.8834754 0.3531223
4 0.3810758 0.9235084 0.2444987
8 0.2621770 0.9567606 0.1630182
16 0.1929048 0.9730444 0.1136515
RMSE was used to select the optimal model using the smallest value.
The final value used for the model was mtry = 16.rf_predictions_binary = predict(rfModel, efw_test)
RMSE(rf_predictions_binary, efw_test$ECONOMIC.FREEDOM)[1] 0.2097298GBT RMSE = 0.2025671
set.seed(1)
gbm <- train(ECONOMIC.FREEDOM~., data=efw_train, method="gbm", trControl=trainControl("cv", number=10), preProc="nzv")Iter TrainDeviance ValidDeviance StepSize Improve
1 0.9656 nan 0.1000 0.0873
2 0.8829 nan 0.1000 0.0790
3 0.8120 nan 0.1000 0.0711
4 0.7491 nan 0.1000 0.0618
5 0.6952 nan 0.1000 0.0547
6 0.6437 nan 0.1000 0.0458
7 0.5981 nan 0.1000 0.0455
8 0.5579 nan 0.1000 0.0380
9 0.5212 nan 0.1000 0.0345
10 0.4846 nan 0.1000 0.0344
20 0.2690 nan 0.1000 0.0148
40 0.1285 nan 0.1000 0.0027
60 0.0807 nan 0.1000 0.0008
80 0.0592 nan 0.1000 0.0005
100 0.0490 nan 0.1000 0.0003
120 0.0437 nan 0.1000 0.0002
140 0.0404 nan 0.1000 0.0001
150 0.0392 nan 0.1000 0.0001
Iter TrainDeviance ValidDeviance StepSize Improve
1 0.9245 nan 0.1000 0.1270
2 0.8168 nan 0.1000 0.1063
3 0.7216 nan 0.1000 0.0909
4 0.6435 nan 0.1000 0.0733
5 0.5768 nan 0.1000 0.0650
6 0.5144 nan 0.1000 0.0589
7 0.4632 nan 0.1000 0.0487
8 0.4193 nan 0.1000 0.0437
9 0.3790 nan 0.1000 0.0393
10 0.3448 nan 0.1000 0.0325
20 0.1622 nan 0.1000 0.0101
40 0.0641 nan 0.1000 0.0022
60 0.0412 nan 0.1000 0.0005
80 0.0345 nan 0.1000 0.0002
100 0.0308 nan 0.1000 0.0001
120 0.0281 nan 0.1000 -0.0000
140 0.0261 nan 0.1000 -0.0000
150 0.0252 nan 0.1000 0.0000
Iter TrainDeviance ValidDeviance StepSize Improve
1 0.9092 nan 0.1000 0.1429
2 0.7855 nan 0.1000 0.1179
3 0.6841 nan 0.1000 0.0956
4 0.5993 nan 0.1000 0.0853
5 0.5251 nan 0.1000 0.0704
6 0.4642 nan 0.1000 0.0592
7 0.4123 nan 0.1000 0.0546
8 0.3686 nan 0.1000 0.0447
9 0.3296 nan 0.1000 0.0356
10 0.2950 nan 0.1000 0.0346
20 0.1212 nan 0.1000 0.0088
40 0.0440 nan 0.1000 0.0011
60 0.0311 nan 0.1000 0.0003
80 0.0268 nan 0.1000 0.0001
100 0.0238 nan 0.1000 0.0001
120 0.0211 nan 0.1000 -0.0001
140 0.0195 nan 0.1000 0.0000
150 0.0187 nan 0.1000 -0.0000
Iter TrainDeviance ValidDeviance StepSize Improve
1 0.9663 nan 0.1000 0.0897
2 0.8869 nan 0.1000 0.0728
3 0.8156 nan 0.1000 0.0711
4 0.7561 nan 0.1000 0.0584
5 0.6972 nan 0.1000 0.0586
6 0.6450 nan 0.1000 0.0479
7 0.5999 nan 0.1000 0.0403
8 0.5579 nan 0.1000 0.0407
9 0.5205 nan 0.1000 0.0375
10 0.4874 nan 0.1000 0.0333
20 0.2695 nan 0.1000 0.0134
40 0.1298 nan 0.1000 0.0034
60 0.0811 nan 0.1000 0.0012
80 0.0592 nan 0.1000 0.0006
100 0.0485 nan 0.1000 0.0003
120 0.0430 nan 0.1000 0.0001
140 0.0397 nan 0.1000 0.0001
150 0.0386 nan 0.1000 0.0001
Iter TrainDeviance ValidDeviance StepSize Improve
1 0.9337 nan 0.1000 0.1277
2 0.8263 nan 0.1000 0.1104
3 0.7303 nan 0.1000 0.0918
4 0.6492 nan 0.1000 0.0818
5 0.5818 nan 0.1000 0.0661
6 0.5194 nan 0.1000 0.0619
7 0.4673 nan 0.1000 0.0512
8 0.4254 nan 0.1000 0.0434
9 0.3860 nan 0.1000 0.0372
10 0.3508 nan 0.1000 0.0347
20 0.1608 nan 0.1000 0.0107
40 0.0638 nan 0.1000 0.0025
60 0.0413 nan 0.1000 0.0006
80 0.0344 nan 0.1000 0.0002
100 0.0308 nan 0.1000 0.0001
120 0.0280 nan 0.1000 -0.0001
140 0.0254 nan 0.1000 -0.0001
150 0.0243 nan 0.1000 0.0000
Iter TrainDeviance ValidDeviance StepSize Improve
1 0.9125 nan 0.1000 0.1429
2 0.7913 nan 0.1000 0.1110
3 0.6897 nan 0.1000 0.0974
4 0.6018 nan 0.1000 0.0850
5 0.5302 nan 0.1000 0.0683
6 0.4696 nan 0.1000 0.0564
7 0.4138 nan 0.1000 0.0575
8 0.3670 nan 0.1000 0.0458
9 0.3274 nan 0.1000 0.0367
10 0.2947 nan 0.1000 0.0315
20 0.1227 nan 0.1000 0.0083
40 0.0445 nan 0.1000 0.0012
60 0.0313 nan 0.1000 0.0002
80 0.0267 nan 0.1000 -0.0000
100 0.0240 nan 0.1000 0.0002
120 0.0218 nan 0.1000 -0.0001
140 0.0203 nan 0.1000 -0.0000
150 0.0195 nan 0.1000 -0.0000
Iter TrainDeviance ValidDeviance StepSize Improve
1 0.9311 nan 0.1000 0.0896
2 0.8542 nan 0.1000 0.0767
3 0.7883 nan 0.1000 0.0658
4 0.7273 nan 0.1000 0.0576
5 0.6730 nan 0.1000 0.0546
6 0.6222 nan 0.1000 0.0512
7 0.5796 nan 0.1000 0.0431
8 0.5430 nan 0.1000 0.0378
9 0.5054 nan 0.1000 0.0359
10 0.4727 nan 0.1000 0.0335
20 0.2594 nan 0.1000 0.0125
40 0.1233 nan 0.1000 0.0033
60 0.0786 nan 0.1000 0.0011
80 0.0583 nan 0.1000 0.0006
100 0.0479 nan 0.1000 0.0001
120 0.0427 nan 0.1000 0.0002
140 0.0395 nan 0.1000 -0.0001
150 0.0385 nan 0.1000 0.0001
Iter TrainDeviance ValidDeviance StepSize Improve
1 0.8969 nan 0.1000 0.1265
2 0.7913 nan 0.1000 0.1012
3 0.6999 nan 0.1000 0.0911
4 0.6238 nan 0.1000 0.0764
5 0.5535 nan 0.1000 0.0691
6 0.4974 nan 0.1000 0.0537
7 0.4467 nan 0.1000 0.0496
8 0.4014 nan 0.1000 0.0405
9 0.3662 nan 0.1000 0.0348
10 0.3328 nan 0.1000 0.0331
20 0.1571 nan 0.1000 0.0105
40 0.0643 nan 0.1000 0.0018
60 0.0407 nan 0.1000 0.0003
80 0.0335 nan 0.1000 0.0002
100 0.0296 nan 0.1000 -0.0000
120 0.0274 nan 0.1000 0.0001
140 0.0252 nan 0.1000 0.0001
150 0.0241 nan 0.1000 0.0000
Iter TrainDeviance ValidDeviance StepSize Improve
1 0.8807 nan 0.1000 0.1379
2 0.7681 nan 0.1000 0.1094
3 0.6661 nan 0.1000 0.0984
4 0.5846 nan 0.1000 0.0865
5 0.5147 nan 0.1000 0.0657
6 0.4527 nan 0.1000 0.0591
7 0.4002 nan 0.1000 0.0509
8 0.3567 nan 0.1000 0.0410
9 0.3182 nan 0.1000 0.0381
10 0.2852 nan 0.1000 0.0321
20 0.1203 nan 0.1000 0.0084
40 0.0443 nan 0.1000 0.0011
60 0.0304 nan 0.1000 0.0002
80 0.0261 nan 0.1000 -0.0001
100 0.0233 nan 0.1000 0.0001
120 0.0206 nan 0.1000 0.0001
140 0.0190 nan 0.1000 -0.0001
150 0.0183 nan 0.1000 -0.0001
Iter TrainDeviance ValidDeviance StepSize Improve
1 0.9704 nan 0.1000 0.0920
2 0.8917 nan 0.1000 0.0785
3 0.8212 nan 0.1000 0.0688
4 0.7591 nan 0.1000 0.0593
5 0.6987 nan 0.1000 0.0603
6 0.6464 nan 0.1000 0.0541
7 0.5993 nan 0.1000 0.0450
8 0.5578 nan 0.1000 0.0412
9 0.5228 nan 0.1000 0.0342
10 0.4881 nan 0.1000 0.0343
20 0.2715 nan 0.1000 0.0139
40 0.1291 nan 0.1000 0.0034
60 0.0823 nan 0.1000 0.0015
80 0.0614 nan 0.1000 0.0007
100 0.0510 nan 0.1000 0.0003
120 0.0456 nan 0.1000 0.0002
140 0.0426 nan 0.1000 -0.0000
150 0.0414 nan 0.1000 0.0001
Iter TrainDeviance ValidDeviance StepSize Improve
1 0.9365 nan 0.1000 0.1320
2 0.8275 nan 0.1000 0.1112
3 0.7345 nan 0.1000 0.0965
4 0.6551 nan 0.1000 0.0785
5 0.5871 nan 0.1000 0.0684
6 0.5245 nan 0.1000 0.0606
7 0.4734 nan 0.1000 0.0491
8 0.4301 nan 0.1000 0.0430
9 0.3900 nan 0.1000 0.0378
10 0.3563 nan 0.1000 0.0335
20 0.1637 nan 0.1000 0.0095
40 0.0664 nan 0.1000 0.0018
60 0.0436 nan 0.1000 0.0004
80 0.0361 nan 0.1000 0.0001
100 0.0322 nan 0.1000 0.0000
120 0.0293 nan 0.1000 0.0001
140 0.0264 nan 0.1000 0.0000
150 0.0254 nan 0.1000 0.0002
Iter TrainDeviance ValidDeviance StepSize Improve
1 0.9192 nan 0.1000 0.1413
2 0.8035 nan 0.1000 0.1209
3 0.6962 nan 0.1000 0.1070
4 0.6101 nan 0.1000 0.0870
5 0.5325 nan 0.1000 0.0794
6 0.4672 nan 0.1000 0.0589
7 0.4129 nan 0.1000 0.0539
8 0.3683 nan 0.1000 0.0443
9 0.3307 nan 0.1000 0.0379
10 0.2968 nan 0.1000 0.0344
20 0.1240 nan 0.1000 0.0074
40 0.0436 nan 0.1000 0.0011
60 0.0304 nan 0.1000 0.0001
80 0.0260 nan 0.1000 0.0002
100 0.0236 nan 0.1000 -0.0001
120 0.0216 nan 0.1000 -0.0000
140 0.0195 nan 0.1000 -0.0000
150 0.0185 nan 0.1000 0.0001
Iter TrainDeviance ValidDeviance StepSize Improve
1 0.9531 nan 0.1000 0.0891
2 0.8782 nan 0.1000 0.0769
3 0.8077 nan 0.1000 0.0711
4 0.7474 nan 0.1000 0.0616
5 0.6902 nan 0.1000 0.0587
6 0.6383 nan 0.1000 0.0493
7 0.5938 nan 0.1000 0.0450
8 0.5551 nan 0.1000 0.0368
9 0.5183 nan 0.1000 0.0379
10 0.4843 nan 0.1000 0.0327
20 0.2666 nan 0.1000 0.0129
40 0.1272 nan 0.1000 0.0037
60 0.0792 nan 0.1000 0.0011
80 0.0568 nan 0.1000 0.0003
100 0.0462 nan 0.1000 0.0003
120 0.0410 nan 0.1000 0.0001
140 0.0379 nan 0.1000 0.0001
150 0.0369 nan 0.1000 -0.0000
Iter TrainDeviance ValidDeviance StepSize Improve
1 0.9204 nan 0.1000 0.1251
2 0.8161 nan 0.1000 0.1064
3 0.7203 nan 0.1000 0.0899
4 0.6409 nan 0.1000 0.0803
5 0.5749 nan 0.1000 0.0690
6 0.5143 nan 0.1000 0.0575
7 0.4645 nan 0.1000 0.0517
8 0.4177 nan 0.1000 0.0442
9 0.3783 nan 0.1000 0.0384
10 0.3455 nan 0.1000 0.0331
20 0.1607 nan 0.1000 0.0100
40 0.0627 nan 0.1000 0.0015
60 0.0382 nan 0.1000 0.0006
80 0.0317 nan 0.1000 0.0001
100 0.0280 nan 0.1000 0.0000
120 0.0257 nan 0.1000 0.0000
140 0.0234 nan 0.1000 0.0000
150 0.0226 nan 0.1000 -0.0000
Iter TrainDeviance ValidDeviance StepSize Improve
1 0.9100 nan 0.1000 0.1438
2 0.7849 nan 0.1000 0.1268
3 0.6821 nan 0.1000 0.0984
4 0.5970 nan 0.1000 0.0842
5 0.5249 nan 0.1000 0.0690
6 0.4642 nan 0.1000 0.0590
7 0.4077 nan 0.1000 0.0525
8 0.3640 nan 0.1000 0.0453
9 0.3255 nan 0.1000 0.0376
10 0.2921 nan 0.1000 0.0327
20 0.1216 nan 0.1000 0.0085
40 0.0435 nan 0.1000 0.0011
60 0.0297 nan 0.1000 0.0002
80 0.0244 nan 0.1000 0.0001
100 0.0215 nan 0.1000 0.0001
120 0.0193 nan 0.1000 -0.0001
140 0.0175 nan 0.1000 -0.0000
150 0.0169 nan 0.1000 0.0001
Iter TrainDeviance ValidDeviance StepSize Improve
1 0.9792 nan 0.1000 0.0929
2 0.8997 nan 0.1000 0.0778
3 0.8279 nan 0.1000 0.0703
4 0.7615 nan 0.1000 0.0671
5 0.7042 nan 0.1000 0.0598
6 0.6530 nan 0.1000 0.0482
7 0.6046 nan 0.1000 0.0473
8 0.5634 nan 0.1000 0.0370
9 0.5238 nan 0.1000 0.0378
10 0.4873 nan 0.1000 0.0347
20 0.2724 nan 0.1000 0.0136
40 0.1297 nan 0.1000 0.0026
60 0.0828 nan 0.1000 0.0016
80 0.0614 nan 0.1000 0.0008
100 0.0509 nan 0.1000 0.0003
120 0.0451 nan 0.1000 0.0001
140 0.0421 nan 0.1000 0.0001
150 0.0410 nan 0.1000 0.0000
Iter TrainDeviance ValidDeviance StepSize Improve
1 0.9448 nan 0.1000 0.1292
2 0.8409 nan 0.1000 0.1050
3 0.7444 nan 0.1000 0.0972
4 0.6643 nan 0.1000 0.0761
5 0.5921 nan 0.1000 0.0725
6 0.5292 nan 0.1000 0.0641
7 0.4774 nan 0.1000 0.0524
8 0.4322 nan 0.1000 0.0456
9 0.3920 nan 0.1000 0.0403
10 0.3582 nan 0.1000 0.0334
20 0.1655 nan 0.1000 0.0102
40 0.0666 nan 0.1000 0.0019
60 0.0439 nan 0.1000 0.0007
80 0.0368 nan 0.1000 0.0000
100 0.0328 nan 0.1000 0.0001
120 0.0298 nan 0.1000 0.0001
140 0.0273 nan 0.1000 0.0001
150 0.0262 nan 0.1000 -0.0001
Iter TrainDeviance ValidDeviance StepSize Improve
1 0.9290 nan 0.1000 0.1494
2 0.8070 nan 0.1000 0.1175
3 0.7018 nan 0.1000 0.1035
4 0.6147 nan 0.1000 0.0874
5 0.5376 nan 0.1000 0.0764
6 0.4751 nan 0.1000 0.0613
7 0.4195 nan 0.1000 0.0502
8 0.3745 nan 0.1000 0.0434
9 0.3331 nan 0.1000 0.0409
10 0.2998 nan 0.1000 0.0353
20 0.1245 nan 0.1000 0.0098
40 0.0470 nan 0.1000 0.0011
60 0.0334 nan 0.1000 0.0001
80 0.0282 nan 0.1000 0.0001
100 0.0245 nan 0.1000 0.0000
120 0.0219 nan 0.1000 -0.0001
140 0.0205 nan 0.1000 -0.0001
150 0.0198 nan 0.1000 0.0001
Iter TrainDeviance ValidDeviance StepSize Improve
1 0.9623 nan 0.1000 0.0887
2 0.8857 nan 0.1000 0.0731
3 0.8116 nan 0.1000 0.0717
4 0.7504 nan 0.1000 0.0602
5 0.6907 nan 0.1000 0.0579
6 0.6392 nan 0.1000 0.0505
7 0.5952 nan 0.1000 0.0441
8 0.5528 nan 0.1000 0.0375
9 0.5151 nan 0.1000 0.0370
10 0.4808 nan 0.1000 0.0332
20 0.2680 nan 0.1000 0.0145
40 0.1272 nan 0.1000 0.0032
60 0.0794 nan 0.1000 0.0014
80 0.0576 nan 0.1000 0.0006
100 0.0475 nan 0.1000 0.0003
120 0.0420 nan 0.1000 0.0001
140 0.0391 nan 0.1000 0.0000
150 0.0380 nan 0.1000 -0.0000
Iter TrainDeviance ValidDeviance StepSize Improve
1 0.9291 nan 0.1000 0.1240
2 0.8173 nan 0.1000 0.1108
3 0.7242 nan 0.1000 0.0919
4 0.6449 nan 0.1000 0.0821
5 0.5724 nan 0.1000 0.0693
6 0.5133 nan 0.1000 0.0571
7 0.4654 nan 0.1000 0.0480
8 0.4218 nan 0.1000 0.0432
9 0.3813 nan 0.1000 0.0403
10 0.3466 nan 0.1000 0.0338
20 0.1649 nan 0.1000 0.0095
40 0.0674 nan 0.1000 0.0023
60 0.0442 nan 0.1000 0.0003
80 0.0370 nan 0.1000 0.0000
100 0.0319 nan 0.1000 0.0001
120 0.0292 nan 0.1000 -0.0001
140 0.0265 nan 0.1000 -0.0000
150 0.0257 nan 0.1000 0.0000
Iter TrainDeviance ValidDeviance StepSize Improve
1 0.9112 nan 0.1000 0.1420
2 0.7915 nan 0.1000 0.1120
3 0.6887 nan 0.1000 0.1069
4 0.6024 nan 0.1000 0.0837
5 0.5279 nan 0.1000 0.0727
6 0.4682 nan 0.1000 0.0580
7 0.4159 nan 0.1000 0.0550
8 0.3684 nan 0.1000 0.0473
9 0.3285 nan 0.1000 0.0387
10 0.2935 nan 0.1000 0.0341
20 0.1254 nan 0.1000 0.0096
40 0.0445 nan 0.1000 0.0011
60 0.0312 nan 0.1000 0.0001
80 0.0266 nan 0.1000 -0.0001
100 0.0234 nan 0.1000 0.0000
120 0.0214 nan 0.1000 0.0000
140 0.0191 nan 0.1000 0.0000
150 0.0183 nan 0.1000 -0.0000
Iter TrainDeviance ValidDeviance StepSize Improve
1 0.9581 nan 0.1000 0.0915
2 0.8819 nan 0.1000 0.0768
3 0.8090 nan 0.1000 0.0732
4 0.7471 nan 0.1000 0.0567
5 0.6899 nan 0.1000 0.0577
6 0.6396 nan 0.1000 0.0494
7 0.5946 nan 0.1000 0.0410
8 0.5542 nan 0.1000 0.0394
9 0.5182 nan 0.1000 0.0352
10 0.4819 nan 0.1000 0.0342
20 0.2649 nan 0.1000 0.0129
40 0.1285 nan 0.1000 0.0033
60 0.0834 nan 0.1000 0.0011
80 0.0632 nan 0.1000 0.0006
100 0.0533 nan 0.1000 -0.0001
120 0.0474 nan 0.1000 0.0002
140 0.0443 nan 0.1000 0.0001
150 0.0432 nan 0.1000 0.0001
Iter TrainDeviance ValidDeviance StepSize Improve
1 0.9186 nan 0.1000 0.1261
2 0.8070 nan 0.1000 0.1094
3 0.7188 nan 0.1000 0.0841
4 0.6385 nan 0.1000 0.0813
5 0.5722 nan 0.1000 0.0622
6 0.5128 nan 0.1000 0.0583
7 0.4625 nan 0.1000 0.0493
8 0.4195 nan 0.1000 0.0433
9 0.3788 nan 0.1000 0.0388
10 0.3467 nan 0.1000 0.0330
20 0.1626 nan 0.1000 0.0090
40 0.0668 nan 0.1000 0.0020
60 0.0439 nan 0.1000 0.0006
80 0.0370 nan 0.1000 0.0001
100 0.0331 nan 0.1000 -0.0001
120 0.0299 nan 0.1000 0.0000
140 0.0273 nan 0.1000 0.0000
150 0.0263 nan 0.1000 0.0001
Iter TrainDeviance ValidDeviance StepSize Improve
1 0.9075 nan 0.1000 0.1405
2 0.7834 nan 0.1000 0.1200
3 0.6871 nan 0.1000 0.0984
4 0.5995 nan 0.1000 0.0814
5 0.5279 nan 0.1000 0.0684
6 0.4635 nan 0.1000 0.0620
7 0.4133 nan 0.1000 0.0503
8 0.3674 nan 0.1000 0.0455
9 0.3272 nan 0.1000 0.0405
10 0.2934 nan 0.1000 0.0311
20 0.1208 nan 0.1000 0.0088
40 0.0455 nan 0.1000 0.0015
60 0.0315 nan 0.1000 0.0002
80 0.0267 nan 0.1000 0.0001
100 0.0233 nan 0.1000 -0.0000
120 0.0213 nan 0.1000 -0.0001
140 0.0196 nan 0.1000 -0.0000
150 0.0188 nan 0.1000 0.0000
Iter TrainDeviance ValidDeviance StepSize Improve
1 0.9468 nan 0.1000 0.0884
2 0.8679 nan 0.1000 0.0796
3 0.7994 nan 0.1000 0.0704
4 0.7405 nan 0.1000 0.0613
5 0.6844 nan 0.1000 0.0575
6 0.6333 nan 0.1000 0.0509
7 0.5882 nan 0.1000 0.0425
8 0.5451 nan 0.1000 0.0404
9 0.5102 nan 0.1000 0.0330
10 0.4752 nan 0.1000 0.0328
20 0.2642 nan 0.1000 0.0114
40 0.1287 nan 0.1000 0.0029
60 0.0830 nan 0.1000 0.0009
80 0.0626 nan 0.1000 0.0007
100 0.0519 nan 0.1000 0.0004
120 0.0471 nan 0.1000 0.0002
140 0.0441 nan 0.1000 0.0001
150 0.0430 nan 0.1000 0.0001
Iter TrainDeviance ValidDeviance StepSize Improve
1 0.9048 nan 0.1000 0.1253
2 0.8012 nan 0.1000 0.1023
3 0.7128 nan 0.1000 0.0875
4 0.6330 nan 0.1000 0.0775
5 0.5666 nan 0.1000 0.0602
6 0.5057 nan 0.1000 0.0609
7 0.4550 nan 0.1000 0.0473
8 0.4141 nan 0.1000 0.0388
9 0.3772 nan 0.1000 0.0372
10 0.3433 nan 0.1000 0.0328
20 0.1599 nan 0.1000 0.0093
40 0.0652 nan 0.1000 0.0019
60 0.0427 nan 0.1000 0.0004
80 0.0352 nan 0.1000 0.0002
100 0.0311 nan 0.1000 0.0001
120 0.0285 nan 0.1000 0.0000
140 0.0261 nan 0.1000 0.0001
150 0.0251 nan 0.1000 -0.0001
Iter TrainDeviance ValidDeviance StepSize Improve
1 0.8970 nan 0.1000 0.1331
2 0.7797 nan 0.1000 0.1164
3 0.6771 nan 0.1000 0.0974
4 0.5946 nan 0.1000 0.0807
5 0.5232 nan 0.1000 0.0705
6 0.4652 nan 0.1000 0.0535
7 0.4130 nan 0.1000 0.0526
8 0.3662 nan 0.1000 0.0442
9 0.3279 nan 0.1000 0.0385
10 0.2923 nan 0.1000 0.0356
20 0.1211 nan 0.1000 0.0087
40 0.0445 nan 0.1000 0.0014
60 0.0312 nan 0.1000 0.0002
80 0.0262 nan 0.1000 -0.0000
100 0.0236 nan 0.1000 -0.0000
120 0.0216 nan 0.1000 -0.0000
140 0.0198 nan 0.1000 -0.0001
150 0.0189 nan 0.1000 0.0000
Iter TrainDeviance ValidDeviance StepSize Improve
1 0.9640 nan 0.1000 0.0926
2 0.8883 nan 0.1000 0.0774
3 0.8159 nan 0.1000 0.0713
4 0.7550 nan 0.1000 0.0601
5 0.6981 nan 0.1000 0.0549
6 0.6447 nan 0.1000 0.0518
7 0.6005 nan 0.1000 0.0435
8 0.5598 nan 0.1000 0.0393
9 0.5197 nan 0.1000 0.0394
10 0.4860 nan 0.1000 0.0334
20 0.2703 nan 0.1000 0.0136
40 0.1300 nan 0.1000 0.0036
60 0.0825 nan 0.1000 0.0010
80 0.0613 nan 0.1000 0.0008
100 0.0509 nan 0.1000 0.0003
120 0.0457 nan 0.1000 0.0001
140 0.0423 nan 0.1000 -0.0000
150 0.0411 nan 0.1000 0.0001
Iter TrainDeviance ValidDeviance StepSize Improve
1 0.9261 nan 0.1000 0.1292
2 0.8184 nan 0.1000 0.1081
3 0.7299 nan 0.1000 0.0888
4 0.6489 nan 0.1000 0.0807
5 0.5795 nan 0.1000 0.0682
6 0.5166 nan 0.1000 0.0624
7 0.4659 nan 0.1000 0.0485
8 0.4216 nan 0.1000 0.0440
9 0.3840 nan 0.1000 0.0366
10 0.3509 nan 0.1000 0.0338
20 0.1649 nan 0.1000 0.0093
40 0.0678 nan 0.1000 0.0020
60 0.0449 nan 0.1000 0.0001
80 0.0376 nan 0.1000 0.0001
100 0.0336 nan 0.1000 -0.0000
120 0.0305 nan 0.1000 0.0001
140 0.0282 nan 0.1000 0.0002
150 0.0274 nan 0.1000 -0.0000
Iter TrainDeviance ValidDeviance StepSize Improve
1 0.9123 nan 0.1000 0.1422
2 0.7937 nan 0.1000 0.1176
3 0.6885 nan 0.1000 0.1063
4 0.6016 nan 0.1000 0.0845
5 0.5291 nan 0.1000 0.0726
6 0.4694 nan 0.1000 0.0584
7 0.4166 nan 0.1000 0.0499
8 0.3684 nan 0.1000 0.0495
9 0.3280 nan 0.1000 0.0357
10 0.2942 nan 0.1000 0.0337
20 0.1199 nan 0.1000 0.0084
40 0.0449 nan 0.1000 0.0010
60 0.0311 nan 0.1000 0.0002
80 0.0262 nan 0.1000 -0.0000
100 0.0232 nan 0.1000 0.0000
120 0.0211 nan 0.1000 0.0001
140 0.0192 nan 0.1000 0.0000
150 0.0184 nan 0.1000 0.0000
Iter TrainDeviance ValidDeviance StepSize Improve
1 0.9075 nan 0.1000 0.1431
2 0.7862 nan 0.1000 0.1232
3 0.6852 nan 0.1000 0.1014
4 0.6011 nan 0.1000 0.0824
5 0.5269 nan 0.1000 0.0686
6 0.4659 nan 0.1000 0.0603
7 0.4123 nan 0.1000 0.0484
8 0.3682 nan 0.1000 0.0460
9 0.3286 nan 0.1000 0.0422
10 0.2953 nan 0.1000 0.0313
20 0.1216 nan 0.1000 0.0088
40 0.0440 nan 0.1000 0.0012
60 0.0305 nan 0.1000 0.0002
80 0.0262 nan 0.1000 -0.0000
100 0.0233 nan 0.1000 0.0000
120 0.0211 nan 0.1000 0.0001
140 0.0198 nan 0.1000 -0.0000
150 0.0191 nan 0.1000 0.0000gbm_predictions_binary = predict(gbm, efw_test)
RMSE(gbm_predictions_binary, efw_test$ECONOMIC.FREEDOM)[1] 0.2025671Normalize variables (scale numeric variables)
meansTrain <- attr(scale(efw_train[, c(1, 3:34)]), "scaled:center")
stddevsTrain <- attr(scale(efw_train[, c(1, 3:34)]), "scaled:scale")
efw_train[, c(1, 3:34)] <- scale(efw_train[, c(1, 3:34)])
efw_test[, c(1, 3:34)] <- scale(efw_test[,c(1, 3:34)], center = meansTrain, scale = stddevsTrain)Split further between train and validation (90% train, 10% validation) and embed categorical variables
library(data.table)
library(mltools)
set.seed(1)
inTrain <- createDataPartition(efw_train$ECONOMIC.FREEDOM, p=0.9, list=FALSE)
train2Label <- efw_train[inTrain, 2]
valLabel <- efw_train[-inTrain, 2]
efw_train2 <- as.data.frame(one_hot(as.data.table(efw_train[inTrain, -2]), cols=c("ISO_code","countries")))
efw_test <- as.data.frame(one_hot(as.data.table(efw_test[, -2]), cols=c("ISO_code","countries")))
efw_val <- as.data.frame(one_hot(as.data.table(efw_train[-inTrain, -2]), cols=c("ISO_code","countries")))
efw_train <- as.data.frame(one_hot(as.data.table(efw_train[, -2]), cols=c("ISO_code","countries")))Neural network models with train/validation
library(keras)
library(tfruns)
runs <- tuning_run("FinalProject.R",
flags = list(
nodes1 = c(64, 128, 392),
nodes2=c(64, 128, 392),
learning_rate = c(0.01, 0.05, 0.001, 0.0001),
batch_size=c(100,200,500),
epochs=c(30,50,100),
activation1=c("relu","sigmoid","tanh"),
activation2=c("relu","sigmoid","tanh"),
dropout1=c(0.05, 0.1, 0.2,0.5) ,
dropout2=c(0.05, 0.1, 0.2,0.5)
),
sample = 0.001)46,656 total combinations of flags (sampled to 46 combinations)yTraining run 1/46 (flags = list(128, 128, 0.01, 100, 100, "tanh", "relu", 0.1, 0.05))
Using run directory runs/2020-05-04T00-52-13Z
> FLAGS <- flags(
+ flag_numeric("nodes1", 128),
+ flag_numeric("nodes2", 128),
+ flag_numeric("batch_size", 100),
+ flag_string("activation1" .... [TRUNCATED]
> model = keras_model_sequential()
> model %>%
+ layer_dense(units=FLAGS$nodes1, activation=FLAGS$activation1, input_shape=dim(efw_train2)[2]) %>%
+ layer_dropout(FLAGS$dropout1) %> .... [TRUNCATED]
> model %>% compile(
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ loss = 'mse',
+ metrics = c('mse')
+ )
> model %>% fit(
+ as.matrix(efw_train2), train2Label,
+ epochs=FLAGS$epochs,
+ batch_size=FLAGS$batch_size,
+ validation_data=list(as.matrix( .... [TRUNCATED]
Train on 3021 samples, validate on 334 samples
Epoch 1/100
100/3021 [..............................] - ETA: 7s - loss: 43.0051 - mse: 43.0051
2600/3021 [========================>.....] - ETA: 0s - loss: 14.0008 - mse: 14.0008
3021/3021 [==============================] - 1s 251us/sample - loss: 12.1758 - mse: 12.1758 - val_loss: 0.8200 - val_mse: 0.8200
Epoch 2/100
100/3021 [..............................] - ETA: 0s - loss: 1.0646 - mse: 1.0646
1700/3021 [===============>..............] - ETA: 0s - loss: 0.8274 - mse: 0.8274
3021/3021 [==============================] - 0s 158us/sample - loss: 0.6158 - mse: 0.6158 - val_loss: 0.2372 - val_mse: 0.2372
Epoch 3/100
100/3021 [..............................] - ETA: 0s - loss: 0.3798 - mse: 0.3798
2300/3021 [=====================>........] - ETA: 0s - loss: 0.2248 - mse: 0.2248
3021/3021 [==============================] - 0s 156us/sample - loss: 0.2186 - mse: 0.2186 - val_loss: 0.1148 - val_mse: 0.1148
Epoch 4/100
100/3021 [..............................] - ETA: 0s - loss: 0.1859 - mse: 0.1859
1600/3021 [==============>...............] - ETA: 0s - loss: 0.1650 - mse: 0.1650
3021/3021 [==============================] - 0s 159us/sample - loss: 0.1675 - mse: 0.1675 - val_loss: 0.0659 - val_mse: 0.0659
Epoch 5/100
100/3021 [..............................] - ETA: 0s - loss: 0.1551 - mse: 0.1551
2200/3021 [====================>.........] - ETA: 0s - loss: 0.1470 - mse: 0.1470
3021/3021 [==============================] - 0s 153us/sample - loss: 0.1511 - mse: 0.1511 - val_loss: 0.0776 - val_mse: 0.0776
Epoch 6/100
100/3021 [..............................] - ETA: 0s - loss: 0.1237 - mse: 0.1237
1400/3021 [============>.................] - ETA: 0s - loss: 0.1464 - mse: 0.1464
3021/3021 [==============================] - 0s 155us/sample - loss: 0.1452 - mse: 0.1452 - val_loss: 0.0795 - val_mse: 0.0795
Epoch 7/100
100/3021 [..............................] - ETA: 0s - loss: 0.1230 - mse: 0.1230
2400/3021 [======================>.......] - ETA: 0s - loss: 0.1300 - mse: 0.1300
3021/3021 [==============================] - 0s 150us/sample - loss: 0.1282 - mse: 0.1282 - val_loss: 0.0704 - val_mse: 0.0704
Epoch 8/100
100/3021 [..............................] - ETA: 0s - loss: 0.1246 - mse: 0.1246
1900/3021 [=================>............] - ETA: 0s - loss: 0.1505 - mse: 0.1505
3021/3021 [==============================] - 0s 149us/sample - loss: 0.1417 - mse: 0.1417 - val_loss: 0.0607 - val_mse: 0.0607
Epoch 9/100
100/3021 [..............................] - ETA: 0s - loss: 0.0986 - mse: 0.0986
1600/3021 [==============>...............] - ETA: 0s - loss: 0.1151 - mse: 0.1151
3021/3021 [==============================] - 0s 157us/sample - loss: 0.1159 - mse: 0.1159 - val_loss: 0.0932 - val_mse: 0.0932
Epoch 10/100
100/3021 [..............................] - ETA: 0s - loss: 0.1483 - mse: 0.1483
2200/3021 [====================>.........] - ETA: 0s - loss: 0.1330 - mse: 0.1330
3021/3021 [==============================] - 0s 149us/sample - loss: 0.1279 - mse: 0.1279 - val_loss: 0.0552 - val_mse: 0.0552
Epoch 11/100
100/3021 [..............................] - ETA: 0s - loss: 0.0911 - mse: 0.0911
1200/3021 [==========>...................] - ETA: 0s - loss: 0.1188 - mse: 0.1188
3021/3021 [==============================] - 1s 170us/sample - loss: 0.1188 - mse: 0.1188 - val_loss: 0.0879 - val_mse: 0.0879
Epoch 12/100
100/3021 [..............................] - ETA: 0s - loss: 0.1248 - mse: 0.1248
2200/3021 [====================>.........] - ETA: 0s - loss: 0.1209 - mse: 0.1209
3021/3021 [==============================] - 0s 152us/sample - loss: 0.1195 - mse: 0.1195 - val_loss: 0.0619 - val_mse: 0.0619
Epoch 13/100
100/3021 [..............................] - ETA: 0s - loss: 0.0744 - mse: 0.0744
2100/3021 [===================>..........] - ETA: 0s - loss: 0.1075 - mse: 0.1075
3021/3021 [==============================] - 0s 150us/sample - loss: 0.1062 - mse: 0.1062 - val_loss: 0.0602 - val_mse: 0.0602
Epoch 14/100
100/3021 [..............................] - ETA: 0s - loss: 0.0966 - mse: 0.0966
2000/3021 [==================>...........] - ETA: 0s - loss: 0.1173 - mse: 0.1173
3021/3021 [==============================] - 0s 155us/sample - loss: 0.1129 - mse: 0.1129 - val_loss: 0.0874 - val_mse: 0.0874
Epoch 15/100
100/3021 [..............................] - ETA: 0s - loss: 0.1122 - mse: 0.1122
2200/3021 [====================>.........] - ETA: 0s - loss: 0.1044 - mse: 0.1044
3021/3021 [==============================] - 0s 150us/sample - loss: 0.1040 - mse: 0.1040 - val_loss: 0.0742 - val_mse: 0.0742
Epoch 16/100
100/3021 [..............................] - ETA: 0s - loss: 0.0840 - mse: 0.0840
2100/3021 [===================>..........] - ETA: 0s - loss: 0.0942 - mse: 0.0942
3021/3021 [==============================] - 0s 159us/sample - loss: 0.0939 - mse: 0.0939 - val_loss: 0.0505 - val_mse: 0.0505
Epoch 17/100
100/3021 [..............................] - ETA: 0s - loss: 0.0781 - mse: 0.0781
1100/3021 [=========>....................] - ETA: 0s - loss: 0.0872 - mse: 0.0872
3021/3021 [==============================] - 0s 164us/sample - loss: 0.0938 - mse: 0.0938 - val_loss: 0.0846 - val_mse: 0.0846
Epoch 18/100
100/3021 [..............................] - ETA: 0s - loss: 0.0766 - mse: 0.0766
1900/3021 [=================>............] - ETA: 0s - loss: 0.0963 - mse: 0.0963
3021/3021 [==============================] - 0s 155us/sample - loss: 0.0958 - mse: 0.0958 - val_loss: 0.1053 - val_mse: 0.1053
Epoch 19/100
100/3021 [..............................] - ETA: 0s - loss: 0.1196 - mse: 0.1196
2400/3021 [======================>.......] - ETA: 0s - loss: 0.1322 - mse: 0.1322
3021/3021 [==============================] - 0s 153us/sample - loss: 0.1302 - mse: 0.1302 - val_loss: 0.0712 - val_mse: 0.0712
Epoch 20/100
100/3021 [..............................] - ETA: 0s - loss: 0.1050 - mse: 0.1050
2200/3021 [====================>.........] - ETA: 0s - loss: 0.0863 - mse: 0.0863
3021/3021 [==============================] - 1s 176us/sample - loss: 0.0875 - mse: 0.0875 - val_loss: 0.0663 - val_mse: 0.0663
Epoch 21/100
100/3021 [..............................] - ETA: 0s - loss: 0.0819 - mse: 0.0819
2100/3021 [===================>..........] - ETA: 0s - loss: 0.0977 - mse: 0.0977
3021/3021 [==============================] - 0s 152us/sample - loss: 0.0920 - mse: 0.0920 - val_loss: 0.0603 - val_mse: 0.0603
Epoch 22/100
100/3021 [..............................] - ETA: 0s - loss: 0.0739 - mse: 0.0739
2500/3021 [=======================>......] - ETA: 0s - loss: 0.0845 - mse: 0.0845
3021/3021 [==============================] - 0s 149us/sample - loss: 0.0877 - mse: 0.0877 - val_loss: 0.0523 - val_mse: 0.0523
Epoch 23/100
100/3021 [..............................] - ETA: 0s - loss: 0.0862 - mse: 0.0862
2300/3021 [=====================>........] - ETA: 0s - loss: 0.0842 - mse: 0.0842
3021/3021 [==============================] - 0s 158us/sample - loss: 0.0858 - mse: 0.0858 - val_loss: 0.0513 - val_mse: 0.0513
Epoch 24/100
100/3021 [..............................] - ETA: 0s - loss: 0.0810 - mse: 0.0810
2000/3021 [==================>...........] - ETA: 0s - loss: 0.0848 - mse: 0.0848
3021/3021 [==============================] - 0s 152us/sample - loss: 0.0863 - mse: 0.0863 - val_loss: 0.0596 - val_mse: 0.0596
Epoch 25/100
100/3021 [..............................] - ETA: 0s - loss: 0.0687 - mse: 0.0687
2200/3021 [====================>.........] - ETA: 0s - loss: 0.0841 - mse: 0.0841
3021/3021 [==============================] - 0s 157us/sample - loss: 0.0815 - mse: 0.0815 - val_loss: 0.0537 - val_mse: 0.0537
Epoch 26/100
100/3021 [..............................] - ETA: 0s - loss: 0.0756 - mse: 0.0756
2300/3021 [=====================>........] - ETA: 0s - loss: 0.0893 - mse: 0.0893
3021/3021 [==============================] - 0s 150us/sample - loss: 0.0845 - mse: 0.0845 - val_loss: 0.0435 - val_mse: 0.0435
Epoch 27/100
100/3021 [..............................] - ETA: 0s - loss: 0.0681 - mse: 0.0681
2400/3021 [======================>.......] - ETA: 0s - loss: 0.0790 - mse: 0.0790
3021/3021 [==============================] - 0s 146us/sample - loss: 0.0801 - mse: 0.0801 - val_loss: 0.0703 - val_mse: 0.0703
Epoch 28/100
100/3021 [..............................] - ETA: 0s - loss: 0.0975 - mse: 0.0975
2300/3021 [=====================>........] - ETA: 0s - loss: 0.0927 - mse: 0.0927
3021/3021 [==============================] - 0s 154us/sample - loss: 0.0899 - mse: 0.0899 - val_loss: 0.0520 - val_mse: 0.0520
Epoch 29/100
100/3021 [..............................] - ETA: 0s - loss: 0.0678 - mse: 0.0678
1800/3021 [================>.............] - ETA: 0s - loss: 0.0811 - mse: 0.0811
3021/3021 [==============================] - 0s 156us/sample - loss: 0.0781 - mse: 0.0781 - val_loss: 0.0519 - val_mse: 0.0519
Epoch 30/100
100/3021 [..............................] - ETA: 0s - loss: 0.0779 - mse: 0.0779
2300/3021 [=====================>........] - ETA: 0s - loss: 0.0773 - mse: 0.0773
3021/3021 [==============================] - 0s 155us/sample - loss: 0.0782 - mse: 0.0782 - val_loss: 0.0777 - val_mse: 0.0777
Epoch 31/100
100/3021 [..............................] - ETA: 0s - loss: 0.1049 - mse: 0.1049
2200/3021 [====================>.........] - ETA: 0s - loss: 0.0939 - mse: 0.0939
3021/3021 [==============================] - 0s 154us/sample - loss: 0.0922 - mse: 0.0922 - val_loss: 0.0940 - val_mse: 0.0940
Epoch 32/100
100/3021 [..............................] - ETA: 0s - loss: 0.1087 - mse: 0.1087
1400/3021 [============>.................] - ETA: 0s - loss: 0.0923 - mse: 0.0923
3021/3021 [==============================] - 0s 160us/sample - loss: 0.0952 - mse: 0.0952 - val_loss: 0.1439 - val_mse: 0.1439
Epoch 33/100
100/3021 [..............................] - ETA: 0s - loss: 0.1694 - mse: 0.1694
2100/3021 [===================>..........] - ETA: 0s - loss: 0.0891 - mse: 0.0891
3021/3021 [==============================] - 0s 160us/sample - loss: 0.0809 - mse: 0.0809 - val_loss: 0.0561 - val_mse: 0.0561
Epoch 34/100
100/3021 [..............................] - ETA: 0s - loss: 0.0589 - mse: 0.0589
2500/3021 [=======================>......] - ETA: 0s - loss: 0.0791 - mse: 0.0791
3021/3021 [==============================] - 0s 151us/sample - loss: 0.0792 - mse: 0.0792 - val_loss: 0.0545 - val_mse: 0.0545
Epoch 35/100
100/3021 [..............................] - ETA: 0s - loss: 0.1048 - mse: 0.1048
2300/3021 [=====================>........] - ETA: 0s - loss: 0.0704 - mse: 0.0704
3021/3021 [==============================] - 0s 149us/sample - loss: 0.0714 - mse: 0.0714 - val_loss: 0.0630 - val_mse: 0.0630
Epoch 36/100
100/3021 [..............................] - ETA: 0s - loss: 0.0852 - mse: 0.0852
1800/3021 [================>.............] - ETA: 0s - loss: 0.0794 - mse: 0.0794
3021/3021 [==============================] - 1s 172us/sample - loss: 0.0780 - mse: 0.0780 - val_loss: 0.0485 - val_mse: 0.0485
Epoch 37/100
100/3021 [..............................] - ETA: 0s - loss: 0.0622 - mse: 0.0622
2200/3021 [====================>.........] - ETA: 0s - loss: 0.0719 - mse: 0.0719
3021/3021 [==============================] - 0s 149us/sample - loss: 0.0728 - mse: 0.0728 - val_loss: 0.0695 - val_mse: 0.0695
Epoch 38/100
100/3021 [..............................] - ETA: 0s - loss: 0.1426 - mse: 0.1426
2500/3021 [=======================>......] - ETA: 0s - loss: 0.0787 - mse: 0.0787
3021/3021 [==============================] - 0s 153us/sample - loss: 0.0775 - mse: 0.0775 - val_loss: 0.0441 - val_mse: 0.0441
Epoch 39/100
100/3021 [..............................] - ETA: 0s - loss: 0.0633 - mse: 0.0633
2400/3021 [======================>.......] - ETA: 0s - loss: 0.0668 - mse: 0.0668
3021/3021 [==============================] - 0s 147us/sample - loss: 0.0670 - mse: 0.0670 - val_loss: 0.0518 - val_mse: 0.0518
Epoch 40/100
100/3021 [..............................] - ETA: 0s - loss: 0.1016 - mse: 0.1016
2500/3021 [=======================>......] - ETA: 0s - loss: 0.0724 - mse: 0.0724
3021/3021 [==============================] - 0s 152us/sample - loss: 0.0698 - mse: 0.0698 - val_loss: 0.0419 - val_mse: 0.0419
Epoch 41/100
100/3021 [..............................] - ETA: 0s - loss: 0.0542 - mse: 0.0542
2100/3021 [===================>..........] - ETA: 0s - loss: 0.0685 - mse: 0.0685
3021/3021 [==============================] - 0s 161us/sample - loss: 0.0683 - mse: 0.0683 - val_loss: 0.0786 - val_mse: 0.0786
Epoch 42/100
100/3021 [..............................] - ETA: 0s - loss: 0.0761 - mse: 0.0761
2100/3021 [===================>..........] - ETA: 0s - loss: 0.0855 - mse: 0.0855
3021/3021 [==============================] - 0s 153us/sample - loss: 0.0828 - mse: 0.0828 - val_loss: 0.0556 - val_mse: 0.0556
Epoch 43/100
100/3021 [..............................] - ETA: 0s - loss: 0.0715 - mse: 0.0715
2400/3021 [======================>.......] - ETA: 0s - loss: 0.0728 - mse: 0.0728
3021/3021 [==============================] - 0s 155us/sample - loss: 0.0719 - mse: 0.0719 - val_loss: 0.0496 - val_mse: 0.0496
Epoch 44/100
100/3021 [..............................] - ETA: 0s - loss: 0.0622 - mse: 0.0622
2600/3021 [========================>.....] - ETA: 0s - loss: 0.0683 - mse: 0.0683
3021/3021 [==============================] - 0s 148us/sample - loss: 0.0685 - mse: 0.0685 - val_loss: 0.0455 - val_mse: 0.0455
Epoch 45/100
100/3021 [..............................] - ETA: 0s - loss: 0.0488 - mse: 0.0488
1700/3021 [===============>..............] - ETA: 0s - loss: 0.0685 - mse: 0.0685
3021/3021 [==============================] - 0s 159us/sample - loss: 0.0720 - mse: 0.0720 - val_loss: 0.0410 - val_mse: 0.0410
Epoch 46/100
100/3021 [..............................] - ETA: 0s - loss: 0.0812 - mse: 0.0812
1700/3021 [===============>..............] - ETA: 0s - loss: 0.0731 - mse: 0.0731
3021/3021 [==============================] - 0s 155us/sample - loss: 0.0738 - mse: 0.0738 - val_loss: 0.0430 - val_mse: 0.0430
Epoch 47/100
100/3021 [..............................] - ETA: 0s - loss: 0.0506 - mse: 0.0506
1400/3021 [============>.................] - ETA: 0s - loss: 0.0616 - mse: 0.0616
3021/3021 [==============================] - 0s 162us/sample - loss: 0.0634 - mse: 0.0634 - val_loss: 0.0379 - val_mse: 0.0379
Epoch 48/100
100/3021 [..............................] - ETA: 0s - loss: 0.0513 - mse: 0.0513
2500/3021 [=======================>......] - ETA: 0s - loss: 0.0637 - mse: 0.0637
3021/3021 [==============================] - 0s 159us/sample - loss: 0.0646 - mse: 0.0646 - val_loss: 0.0646 - val_mse: 0.0646
Epoch 49/100
100/3021 [..............................] - ETA: 0s - loss: 0.0726 - mse: 0.0726
1900/3021 [=================>............] - ETA: 0s - loss: 0.0739 - mse: 0.0739
3021/3021 [==============================] - 0s 158us/sample - loss: 0.0710 - mse: 0.0710 - val_loss: 0.0406 - val_mse: 0.0406
Epoch 50/100
100/3021 [..............................] - ETA: 0s - loss: 0.0576 - mse: 0.0576
2200/3021 [====================>.........] - ETA: 0s - loss: 0.0834 - mse: 0.0834
3021/3021 [==============================] - 0s 153us/sample - loss: 0.0801 - mse: 0.0801 - val_loss: 0.0434 - val_mse: 0.0434
Epoch 51/100
100/3021 [..............................] - ETA: 0s - loss: 0.0690 - mse: 0.0690
2500/3021 [=======================>......] - ETA: 0s - loss: 0.0701 - mse: 0.0701
3021/3021 [==============================] - 0s 159us/sample - loss: 0.0694 - mse: 0.0694 - val_loss: 0.0383 - val_mse: 0.0383
Epoch 52/100
100/3021 [..............................] - ETA: 0s - loss: 0.0583 - mse: 0.0583
1700/3021 [===============>..............] - ETA: 0s - loss: 0.0686 - mse: 0.0686
3021/3021 [==============================] - 1s 194us/sample - loss: 0.0714 - mse: 0.0714 - val_loss: 0.0527 - val_mse: 0.0527
Epoch 53/100
100/3021 [..............................] - ETA: 0s - loss: 0.0577 - mse: 0.0577
1600/3021 [==============>...............] - ETA: 0s - loss: 0.0677 - mse: 0.0677
3021/3021 [==============================] - 1s 205us/sample - loss: 0.0663 - mse: 0.0663 - val_loss: 0.0438 - val_mse: 0.0438
Epoch 54/100
100/3021 [..............................] - ETA: 0s - loss: 0.0683 - mse: 0.0683
1500/3021 [=============>................] - ETA: 0s - loss: 0.0641 - mse: 0.0641
2700/3021 [=========================>....] - ETA: 0s - loss: 0.0681 - mse: 0.0681
3021/3021 [==============================] - 1s 207us/sample - loss: 0.0677 - mse: 0.0677 - val_loss: 0.0458 - val_mse: 0.0458
Epoch 55/100
100/3021 [..............................] - ETA: 0s - loss: 0.0672 - mse: 0.0672
2100/3021 [===================>..........] - ETA: 0s - loss: 0.0648 - mse: 0.0648
3021/3021 [==============================] - 0s 157us/sample - loss: 0.0654 - mse: 0.0654 - val_loss: 0.0377 - val_mse: 0.0377
Epoch 56/100
100/3021 [..............................] - ETA: 0s - loss: 0.0481 - mse: 0.0481
2300/3021 [=====================>........] - ETA: 0s - loss: 0.0605 - mse: 0.0605
3021/3021 [==============================] - 0s 154us/sample - loss: 0.0603 - mse: 0.0603 - val_loss: 0.0602 - val_mse: 0.0602
Epoch 57/100
100/3021 [..............................] - ETA: 0s - loss: 0.0552 - mse: 0.0552
2300/3021 [=====================>........] - ETA: 0s - loss: 0.0740 - mse: 0.0740
3021/3021 [==============================] - 0s 153us/sample - loss: 0.0750 - mse: 0.0750 - val_loss: 0.0763 - val_mse: 0.0763
Epoch 58/100
100/3021 [..............................] - ETA: 0s - loss: 0.0844 - mse: 0.0844
2300/3021 [=====================>........] - ETA: 0s - loss: 0.0833 - mse: 0.0833
3021/3021 [==============================] - 0s 154us/sample - loss: 0.0789 - mse: 0.0789 - val_loss: 0.0652 - val_mse: 0.0652
Epoch 59/100
100/3021 [..............................] - ETA: 0s - loss: 0.1072 - mse: 0.1072
2100/3021 [===================>..........] - ETA: 0s - loss: 0.0716 - mse: 0.0716
3021/3021 [==============================] - 1s 184us/sample - loss: 0.0686 - mse: 0.0686 - val_loss: 0.0547 - val_mse: 0.0547
Epoch 60/100
100/3021 [..............................] - ETA: 0s - loss: 0.0758 - mse: 0.0758
1500/3021 [=============>................] - ETA: 0s - loss: 0.0722 - mse: 0.0722
3021/3021 [==============================] - 1s 175us/sample - loss: 0.0669 - mse: 0.0669 - val_loss: 0.0377 - val_mse: 0.0377
Epoch 61/100
100/3021 [..............................] - ETA: 0s - loss: 0.0604 - mse: 0.0604
1400/3021 [============>.................] - ETA: 0s - loss: 0.0616 - mse: 0.0616
2700/3021 [=========================>....] - ETA: 0s - loss: 0.0615 - mse: 0.0615
3021/3021 [==============================] - 1s 224us/sample - loss: 0.0617 - mse: 0.0617 - val_loss: 0.0547 - val_mse: 0.0547
Epoch 62/100
100/3021 [..............................] - ETA: 0s - loss: 0.0577 - mse: 0.0577
1400/3021 [============>.................] - ETA: 0s - loss: 0.0694 - mse: 0.0694
3021/3021 [==============================] - 1s 174us/sample - loss: 0.0654 - mse: 0.0654 - val_loss: 0.0428 - val_mse: 0.0428
Epoch 63/100
100/3021 [..............................] - ETA: 0s - loss: 0.0503 - mse: 0.0503
2200/3021 [====================>.........] - ETA: 0s - loss: 0.0694 - mse: 0.0694
3021/3021 [==============================] - 1s 176us/sample - loss: 0.0702 - mse: 0.0702 - val_loss: 0.0453 - val_mse: 0.0453
Epoch 64/100
100/3021 [..............................] - ETA: 0s - loss: 0.0520 - mse: 0.0520
1800/3021 [================>.............] - ETA: 0s - loss: 0.0620 - mse: 0.0620
3021/3021 [==============================] - 0s 153us/sample - loss: 0.0638 - mse: 0.0638 - val_loss: 0.0408 - val_mse: 0.0408
Epoch 65/100
100/3021 [..............................] - ETA: 0s - loss: 0.0623 - mse: 0.0623
1300/3021 [===========>..................] - ETA: 0s - loss: 0.0614 - mse: 0.0614
2900/3021 [===========================>..] - ETA: 0s - loss: 0.0638 - mse: 0.0638
3021/3021 [==============================] - 1s 205us/sample - loss: 0.0628 - mse: 0.0628 - val_loss: 0.0418 - val_mse: 0.0418
Epoch 66/100
100/3021 [..............................] - ETA: 0s - loss: 0.0453 - mse: 0.0453
1900/3021 [=================>............] - ETA: 0s - loss: 0.0567 - mse: 0.0567
3021/3021 [==============================] - 1s 185us/sample - loss: 0.0582 - mse: 0.0582 - val_loss: 0.0491 - val_mse: 0.0491
Epoch 67/100
100/3021 [..............................] - ETA: 0s - loss: 0.0967 - mse: 0.0967
1600/3021 [==============>...............] - ETA: 0s - loss: 0.0541 - mse: 0.0541
3021/3021 [==============================] - 1s 191us/sample - loss: 0.0544 - mse: 0.0544 - val_loss: 0.0428 - val_mse: 0.0428
Epoch 68/100
100/3021 [..............................] - ETA: 0s - loss: 0.0432 - mse: 0.0432
1600/3021 [==============>...............] - ETA: 0s - loss: 0.0574 - mse: 0.0574
3021/3021 [==============================] - 1s 175us/sample - loss: 0.0550 - mse: 0.0550 - val_loss: 0.0448 - val_mse: 0.0448
Epoch 69/100
100/3021 [..............................] - ETA: 0s - loss: 0.0534 - mse: 0.0534
1800/3021 [================>.............] - ETA: 0s - loss: 0.0641 - mse: 0.0641
3021/3021 [==============================] - 1s 180us/sample - loss: 0.0620 - mse: 0.0620 - val_loss: 0.0425 - val_mse: 0.0425
Epoch 70/100
100/3021 [..............................] - ETA: 0s - loss: 0.0698 - mse: 0.0698
2100/3021 [===================>..........] - ETA: 0s - loss: 0.0583 - mse: 0.0583
3021/3021 [==============================] - 1s 171us/sample - loss: 0.0583 - mse: 0.0583 - val_loss: 0.0475 - val_mse: 0.0475
Epoch 71/100
100/3021 [..............................] - ETA: 0s - loss: 0.0584 - mse: 0.0584
1800/3021 [================>.............] - ETA: 0s - loss: 0.0580 - mse: 0.0580
3021/3021 [==============================] - 0s 156us/sample - loss: 0.0603 - mse: 0.0603 - val_loss: 0.0700 - val_mse: 0.0700
Epoch 72/100
100/3021 [..............................] - ETA: 0s - loss: 0.0739 - mse: 0.0739
2300/3021 [=====================>........] - ETA: 0s - loss: 0.0653 - mse: 0.0653
3021/3021 [==============================] - 0s 159us/sample - loss: 0.0639 - mse: 0.0639 - val_loss: 0.0443 - val_mse: 0.0443
Epoch 73/100
100/3021 [..............................] - ETA: 0s - loss: 0.0432 - mse: 0.0432
2100/3021 [===================>..........] - ETA: 0s - loss: 0.0512 - mse: 0.0512
3021/3021 [==============================] - 0s 158us/sample - loss: 0.0537 - mse: 0.0537 - val_loss: 0.0755 - val_mse: 0.0755
Epoch 74/100
100/3021 [..............................] - ETA: 0s - loss: 0.0794 - mse: 0.0794
2100/3021 [===================>..........] - ETA: 0s - loss: 0.0659 - mse: 0.0659
3021/3021 [==============================] - 1s 173us/sample - loss: 0.0606 - mse: 0.0606 - val_loss: 0.0427 - val_mse: 0.0427
Epoch 75/100
100/3021 [..............................] - ETA: 0s - loss: 0.0594 - mse: 0.0594
1800/3021 [================>.............] - ETA: 0s - loss: 0.0565 - mse: 0.0565
3021/3021 [==============================] - 1s 194us/sample - loss: 0.0573 - mse: 0.0573 - val_loss: 0.0639 - val_mse: 0.0639
Epoch 76/100
100/3021 [..............................] - ETA: 0s - loss: 0.0666 - mse: 0.0666
2100/3021 [===================>..........] - ETA: 0s - loss: 0.0653 - mse: 0.0653
3021/3021 [==============================] - 0s 159us/sample - loss: 0.0638 - mse: 0.0638 - val_loss: 0.0559 - val_mse: 0.0559
Epoch 77/100
100/3021 [..............................] - ETA: 0s - loss: 0.0472 - mse: 0.0472
2300/3021 [=====================>........] - ETA: 0s - loss: 0.0703 - mse: 0.0703
3021/3021 [==============================] - 0s 154us/sample - loss: 0.0692 - mse: 0.0692 - val_loss: 0.0484 - val_mse: 0.0484
Epoch 78/100
100/3021 [..............................] - ETA: 0s - loss: 0.0689 - mse: 0.0689
1800/3021 [================>.............] - ETA: 0s - loss: 0.0649 - mse: 0.0649
3021/3021 [==============================] - 0s 159us/sample - loss: 0.0613 - mse: 0.0613 - val_loss: 0.0753 - val_mse: 0.0753
Epoch 79/100
100/3021 [..............................] - ETA: 0s - loss: 0.0891 - mse: 0.0891
1900/3021 [=================>............] - ETA: 0s - loss: 0.0689 - mse: 0.0689
3021/3021 [==============================] - 1s 183us/sample - loss: 0.0660 - mse: 0.0660 - val_loss: 0.0600 - val_mse: 0.0600
Epoch 80/100
100/3021 [..............................] - ETA: 0s - loss: 0.0851 - mse: 0.0851
2100/3021 [===================>..........] - ETA: 0s - loss: 0.0633 - mse: 0.0633
3021/3021 [==============================] - 1s 177us/sample - loss: 0.0598 - mse: 0.0598 - val_loss: 0.0437 - val_mse: 0.0437
Epoch 81/100
100/3021 [..............................] - ETA: 0s - loss: 0.0423 - mse: 0.0423
1400/3021 [============>.................] - ETA: 0s - loss: 0.0493 - mse: 0.0493
3021/3021 [==============================] - 0s 153us/sample - loss: 0.0508 - mse: 0.0508 - val_loss: 0.0477 - val_mse: 0.0477
Epoch 82/100
100/3021 [..............................] - ETA: 0s - loss: 0.0512 - mse: 0.0512
1900/3021 [=================>............] - ETA: 0s - loss: 0.0558 - mse: 0.0558
3021/3021 [==============================] - 0s 159us/sample - loss: 0.0544 - mse: 0.0544 - val_loss: 0.0506 - val_mse: 0.0506
Epoch 83/100
100/3021 [..............................] - ETA: 0s - loss: 0.0740 - mse: 0.0740
2100/3021 [===================>..........] - ETA: 0s - loss: 0.0602 - mse: 0.0602
3021/3021 [==============================] - 0s 157us/sample - loss: 0.0578 - mse: 0.0578 - val_loss: 0.0469 - val_mse: 0.0469
Epoch 84/100
100/3021 [..............................] - ETA: 0s - loss: 0.0509 - mse: 0.0509
1600/3021 [==============>...............] - ETA: 0s - loss: 0.0541 - mse: 0.0541
3021/3021 [==============================] - 0s 164us/sample - loss: 0.0539 - mse: 0.0539 - val_loss: 0.0667 - val_mse: 0.0667
Epoch 85/100
100/3021 [..............................] - ETA: 0s - loss: 0.0953 - mse: 0.0953
2000/3021 [==================>...........] - ETA: 0s - loss: 0.0611 - mse: 0.0611
3021/3021 [==============================] - 0s 163us/sample - loss: 0.0604 - mse: 0.0604 - val_loss: 0.0709 - val_mse: 0.0709
Epoch 86/100
100/3021 [..............................] - ETA: 0s - loss: 0.0814 - mse: 0.0814
2100/3021 [===================>..........] - ETA: 0s - loss: 0.0722 - mse: 0.0722
3021/3021 [==============================] - 0s 160us/sample - loss: 0.0664 - mse: 0.0664 - val_loss: 0.0531 - val_mse: 0.0531
Epoch 87/100
100/3021 [..............................] - ETA: 0s - loss: 0.0636 - mse: 0.0636
1600/3021 [==============>...............] - ETA: 0s - loss: 0.0619 - mse: 0.0619
3021/3021 [==============================] - 1s 171us/sample - loss: 0.0621 - mse: 0.0621 - val_loss: 0.0440 - val_mse: 0.0440
Epoch 88/100
100/3021 [..............................] - ETA: 0s - loss: 0.0710 - mse: 0.0710
1800/3021 [================>.............] - ETA: 0s - loss: 0.0539 - mse: 0.0539
3021/3021 [==============================] - 0s 158us/sample - loss: 0.0531 - mse: 0.0531 - val_loss: 0.0420 - val_mse: 0.0420
Epoch 89/100
100/3021 [..............................] - ETA: 0s - loss: 0.0502 - mse: 0.0502
2200/3021 [====================>.........] - ETA: 0s - loss: 0.0519 - mse: 0.0519
3021/3021 [==============================] - 0s 154us/sample - loss: 0.0537 - mse: 0.0537 - val_loss: 0.0733 - val_mse: 0.0733
Epoch 90/100
100/3021 [..............................] - ETA: 0s - loss: 0.0772 - mse: 0.0772
2100/3021 [===================>..........] - ETA: 0s - loss: 0.0628 - mse: 0.0628
3021/3021 [==============================] - 1s 175us/sample - loss: 0.0590 - mse: 0.0590 - val_loss: 0.0395 - val_mse: 0.0395
Epoch 91/100
100/3021 [..............................] - ETA: 0s - loss: 0.0452 - mse: 0.0452
1400/3021 [============>.................] - ETA: 0s - loss: 0.0571 - mse: 0.0571
3021/3021 [==============================] - 0s 162us/sample - loss: 0.0606 - mse: 0.0606 - val_loss: 0.0409 - val_mse: 0.0409
Epoch 92/100
100/3021 [..............................] - ETA: 0s - loss: 0.0447 - mse: 0.0447
2200/3021 [====================>.........] - ETA: 0s - loss: 0.0525 - mse: 0.0525
3021/3021 [==============================] - 0s 155us/sample - loss: 0.0512 - mse: 0.0512 - val_loss: 0.0418 - val_mse: 0.0418
Epoch 93/100
100/3021 [..............................] - ETA: 0s - loss: 0.0445 - mse: 0.0445
2500/3021 [=======================>......] - ETA: 0s - loss: 0.0512 - mse: 0.0512
3021/3021 [==============================] - 0s 155us/sample - loss: 0.0520 - mse: 0.0520 - val_loss: 0.0451 - val_mse: 0.0451
Epoch 94/100
100/3021 [..............................] - ETA: 0s - loss: 0.0506 - mse: 0.0506
2300/3021 [=====================>........] - ETA: 0s - loss: 0.0463 - mse: 0.0463
3021/3021 [==============================] - 1s 184us/sample - loss: 0.0471 - mse: 0.0471 - val_loss: 0.0508 - val_mse: 0.0508
Epoch 95/100
100/3021 [..............................] - ETA: 0s - loss: 0.0704 - mse: 0.0704
1100/3021 [=========>....................] - ETA: 0s - loss: 0.0543 - mse: 0.0543
3021/3021 [==============================] - 0s 164us/sample - loss: 0.0503 - mse: 0.0503 - val_loss: 0.0532 - val_mse: 0.0532
Epoch 96/100
100/3021 [..............................] - ETA: 0s - loss: 0.0509 - mse: 0.0509
1500/3021 [=============>................] - ETA: 0s - loss: 0.0514 - mse: 0.0514
3021/3021 [==============================] - 1s 171us/sample - loss: 0.0569 - mse: 0.0569 - val_loss: 0.0408 - val_mse: 0.0408
Epoch 97/100
100/3021 [..............................] - ETA: 0s - loss: 0.0377 - mse: 0.0377
2000/3021 [==================>...........] - ETA: 0s - loss: 0.0546 - mse: 0.0546
3021/3021 [==============================] - 0s 155us/sample - loss: 0.0548 - mse: 0.0548 - val_loss: 0.0440 - val_mse: 0.0440
Epoch 98/100
100/3021 [..............................] - ETA: 0s - loss: 0.0605 - mse: 0.0605
2400/3021 [======================>.......] - ETA: 0s - loss: 0.0537 - mse: 0.0537
3021/3021 [==============================] - 0s 163us/sample - loss: 0.0558 - mse: 0.0558 - val_loss: 0.0429 - val_mse: 0.0429
Epoch 99/100
100/3021 [..............................] - ETA: 0s - loss: 0.0407 - mse: 0.0407
2400/3021 [======================>.......] - ETA: 0s - loss: 0.0552 - mse: 0.0552
3021/3021 [==============================] - 0s 156us/sample - loss: 0.0569 - mse: 0.0569 - val_loss: 0.0476 - val_mse: 0.0476
Epoch 100/100
100/3021 [..............................] - ETA: 0s - loss: 0.0581 - mse: 0.0581
2300/3021 [=====================>........] - ETA: 0s - loss: 0.0610 - mse: 0.0610
3021/3021 [==============================] - 0s 164us/sample - loss: 0.0572 - mse: 0.0572 - val_loss: 0.0513 - val_mse: 0.0513Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-05-04T00-52-13Z
Training run 2/46 (flags = list(64, 392, 0.001, 500, 100, "tanh", "sigmoid", 0.1, 0.1))
Using run directory runs/2020-05-04T00-53-06Z
> FLAGS <- flags(
+ flag_numeric("nodes1", 128),
+ flag_numeric("nodes2", 128),
+ flag_numeric("batch_size", 100),
+ flag_string("activation1" .... [TRUNCATED]
> model = keras_model_sequential()
> model %>%
+ layer_dense(units=FLAGS$nodes1, activation=FLAGS$activation1, input_shape=dim(efw_train2)[2]) %>%
+ layer_dropout(FLAGS$dropout1) %> .... [TRUNCATED]
> model %>% compile(
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ loss = 'mse',
+ metrics = c('mse')
+ )
> model %>% fit(
+ as.matrix(efw_train2), train2Label,
+ epochs=FLAGS$epochs,
+ batch_size=FLAGS$batch_size,
+ validation_data=list(as.matrix( .... [TRUNCATED]
Train on 3021 samples, validate on 334 samples
Epoch 1/100
500/3021 [===>..........................] - ETA: 1s - loss: 43.9285 - mse: 43.9285
3021/3021 [==============================] - 1s 257us/sample - loss: 42.3473 - mse: 42.3473 - val_loss: 41.8376 - val_mse: 41.8376
Epoch 2/100
500/3021 [===>..........................] - ETA: 0s - loss: 40.2541 - mse: 40.2541
3021/3021 [==============================] - 0s 161us/sample - loss: 39.4360 - mse: 39.4360 - val_loss: 39.7333 - val_mse: 39.7333
Epoch 3/100
500/3021 [===>..........................] - ETA: 0s - loss: 38.3397 - mse: 38.3397
3021/3021 [==============================] - 0s 147us/sample - loss: 37.2303 - mse: 37.2303 - val_loss: 37.4463 - val_mse: 37.4463
Epoch 4/100
500/3021 [===>..........................] - ETA: 0s - loss: 35.2426 - mse: 35.2426
3021/3021 [==============================] - 0s 146us/sample - loss: 34.8757 - mse: 34.8757 - val_loss: 34.9030 - val_mse: 34.9030
Epoch 5/100
500/3021 [===>..........................] - ETA: 0s - loss: 33.6854 - mse: 33.6854
3021/3021 [==============================] - 0s 148us/sample - loss: 32.5385 - mse: 32.5385 - val_loss: 32.3607 - val_mse: 32.3607
Epoch 6/100
500/3021 [===>..........................] - ETA: 0s - loss: 31.0609 - mse: 31.0609
3021/3021 [==============================] - 0s 139us/sample - loss: 30.1253 - mse: 30.1253 - val_loss: 29.8781 - val_mse: 29.8781
Epoch 7/100
500/3021 [===>..........................] - ETA: 0s - loss: 28.4430 - mse: 28.4430
3021/3021 [==============================] - 0s 128us/sample - loss: 27.6347 - mse: 27.6347 - val_loss: 27.3337 - val_mse: 27.3337
Epoch 8/100
500/3021 [===>..........................] - ETA: 0s - loss: 26.1487 - mse: 26.1487
3021/3021 [==============================] - 0s 149us/sample - loss: 25.0776 - mse: 25.0776 - val_loss: 24.7063 - val_mse: 24.7063
Epoch 9/100
500/3021 [===>..........................] - ETA: 0s - loss: 23.4803 - mse: 23.4803
3021/3021 [==============================] - 0s 135us/sample - loss: 22.4594 - mse: 22.4594 - val_loss: 22.0480 - val_mse: 22.0480
Epoch 10/100
500/3021 [===>..........................] - ETA: 0s - loss: 21.0963 - mse: 21.0963
3021/3021 [==============================] - 1s 206us/sample - loss: 19.9090 - mse: 19.9090 - val_loss: 19.3104 - val_mse: 19.3104
Epoch 11/100
500/3021 [===>..........................] - ETA: 0s - loss: 18.4162 - mse: 18.4162
3021/3021 [==============================] - 0s 154us/sample - loss: 17.3329 - mse: 17.3329 - val_loss: 16.6777 - val_mse: 16.6777
Epoch 12/100
500/3021 [===>..........................] - ETA: 0s - loss: 15.4765 - mse: 15.4765
3021/3021 [==============================] - 0s 151us/sample - loss: 14.8396 - mse: 14.8396 - val_loss: 14.2065 - val_mse: 14.2065
Epoch 13/100
500/3021 [===>..........................] - ETA: 0s - loss: 13.5643 - mse: 13.5643
3021/3021 [==============================] - 0s 131us/sample - loss: 12.5658 - mse: 12.5658 - val_loss: 11.8702 - val_mse: 11.8702
Epoch 14/100
500/3021 [===>..........................] - ETA: 0s - loss: 11.3708 - mse: 11.3708
3021/3021 [==============================] - 0s 149us/sample - loss: 10.3472 - mse: 10.3472 - val_loss: 9.7135 - val_mse: 9.7135
Epoch 15/100
500/3021 [===>..........................] - ETA: 0s - loss: 9.2984 - mse: 9.2984
3021/3021 [==============================] - 0s 133us/sample - loss: 8.3079 - mse: 8.3080 - val_loss: 7.7813 - val_mse: 7.7813
Epoch 16/100
500/3021 [===>..........................] - ETA: 0s - loss: 7.2256 - mse: 7.2256
3021/3021 [==============================] - 0s 144us/sample - loss: 6.6308 - mse: 6.6308 - val_loss: 6.1079 - val_mse: 6.1079
Epoch 17/100
500/3021 [===>..........................] - ETA: 0s - loss: 5.4393 - mse: 5.4393
3021/3021 [==============================] - 0s 142us/sample - loss: 5.0270 - mse: 5.0270 - val_loss: 4.6807 - val_mse: 4.6807
Epoch 18/100
500/3021 [===>..........................] - ETA: 0s - loss: 4.1828 - mse: 4.1828
3021/3021 [==============================] - 0s 135us/sample - loss: 3.8138 - mse: 3.8138 - val_loss: 3.5226 - val_mse: 3.5226
Epoch 19/100
500/3021 [===>..........................] - ETA: 0s - loss: 3.1884 - mse: 3.1884
3021/3021 [==============================] - 0s 147us/sample - loss: 2.8331 - mse: 2.8331 - val_loss: 2.5867 - val_mse: 2.5867
Epoch 20/100
500/3021 [===>..........................] - ETA: 0s - loss: 2.3946 - mse: 2.3946
3021/3021 [==============================] - 0s 139us/sample - loss: 2.0315 - mse: 2.0315 - val_loss: 1.8486 - val_mse: 1.8486
Epoch 21/100
500/3021 [===>..........................] - ETA: 0s - loss: 1.6424 - mse: 1.6424
3021/3021 [==============================] - 0s 139us/sample - loss: 1.4689 - mse: 1.4689 - val_loss: 1.2873 - val_mse: 1.2873
Epoch 22/100
500/3021 [===>..........................] - ETA: 0s - loss: 1.2784 - mse: 1.2784
3021/3021 [==============================] - 0s 139us/sample - loss: 1.0395 - mse: 1.0395 - val_loss: 0.9076 - val_mse: 0.9076
Epoch 23/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.7837 - mse: 0.7837
3021/3021 [==============================] - 0s 147us/sample - loss: 0.7524 - mse: 0.7524 - val_loss: 0.6449 - val_mse: 0.6449
Epoch 24/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.6222 - mse: 0.6222
3021/3021 [==============================] - 0s 146us/sample - loss: 0.5579 - mse: 0.5579 - val_loss: 0.4692 - val_mse: 0.4692
Epoch 25/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.4455 - mse: 0.4455
3021/3021 [==============================] - 0s 136us/sample - loss: 0.4127 - mse: 0.4127 - val_loss: 0.3509 - val_mse: 0.3509
Epoch 26/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.3942 - mse: 0.3942
3021/3021 [==============================] - 0s 139us/sample - loss: 0.3519 - mse: 0.3519 - val_loss: 0.2734 - val_mse: 0.2734
Epoch 27/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.3103 - mse: 0.3103
3021/3021 [==============================] - 0s 141us/sample - loss: 0.2963 - mse: 0.2963 - val_loss: 0.2249 - val_mse: 0.2249
Epoch 28/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.2829 - mse: 0.2829
3021/3021 [==============================] - 0s 142us/sample - loss: 0.2765 - mse: 0.2765 - val_loss: 0.1927 - val_mse: 0.1927
Epoch 29/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.2451 - mse: 0.2451
3021/3021 [==============================] - 0s 133us/sample - loss: 0.2542 - mse: 0.2542 - val_loss: 0.1701 - val_mse: 0.1701
Epoch 30/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.2586 - mse: 0.2586
3021/3021 [==============================] - 0s 133us/sample - loss: 0.2399 - mse: 0.2399 - val_loss: 0.1508 - val_mse: 0.1508
Epoch 31/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.2275 - mse: 0.2275
3021/3021 [==============================] - 0s 142us/sample - loss: 0.2221 - mse: 0.2221 - val_loss: 0.1351 - val_mse: 0.1351
Epoch 32/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.2049 - mse: 0.2049
3021/3021 [==============================] - 0s 133us/sample - loss: 0.2125 - mse: 0.2125 - val_loss: 0.1254 - val_mse: 0.1254
Epoch 33/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.2191 - mse: 0.2191
3021/3021 [==============================] - 0s 135us/sample - loss: 0.2078 - mse: 0.2078 - val_loss: 0.1154 - val_mse: 0.1154
Epoch 34/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.2155 - mse: 0.2155
3021/3021 [==============================] - 0s 138us/sample - loss: 0.2005 - mse: 0.2005 - val_loss: 0.1078 - val_mse: 0.1078
Epoch 35/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.2199 - mse: 0.2199
3021/3021 [==============================] - 0s 143us/sample - loss: 0.1975 - mse: 0.1975 - val_loss: 0.1004 - val_mse: 0.1004
Epoch 36/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.2048 - mse: 0.2048
3021/3021 [==============================] - 0s 159us/sample - loss: 0.1906 - mse: 0.1906 - val_loss: 0.0956 - val_mse: 0.0956
Epoch 37/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1893 - mse: 0.1893
3021/3021 [==============================] - 0s 146us/sample - loss: 0.1957 - mse: 0.1957 - val_loss: 0.0933 - val_mse: 0.0933
Epoch 38/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1872 - mse: 0.1872
3021/3021 [==============================] - 1s 169us/sample - loss: 0.1793 - mse: 0.1793 - val_loss: 0.0880 - val_mse: 0.0880
Epoch 39/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.2269 - mse: 0.2269
3021/3021 [==============================] - 0s 146us/sample - loss: 0.1861 - mse: 0.1861 - val_loss: 0.0810 - val_mse: 0.0810
Epoch 40/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1653 - mse: 0.1653
3021/3021 [==============================] - 0s 144us/sample - loss: 0.1746 - mse: 0.1746 - val_loss: 0.0767 - val_mse: 0.0767
Epoch 41/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1914 - mse: 0.1914
3021/3021 [==============================] - 0s 134us/sample - loss: 0.1731 - mse: 0.1731 - val_loss: 0.0744 - val_mse: 0.0744
Epoch 42/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1841 - mse: 0.1841
3021/3021 [==============================] - 0s 139us/sample - loss: 0.1727 - mse: 0.1727 - val_loss: 0.0714 - val_mse: 0.0714
Epoch 43/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1702 - mse: 0.1702
3021/3021 [==============================] - 0s 137us/sample - loss: 0.1631 - mse: 0.1631 - val_loss: 0.0681 - val_mse: 0.0681
Epoch 44/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1521 - mse: 0.1521
3021/3021 [==============================] - 0s 135us/sample - loss: 0.1658 - mse: 0.1658 - val_loss: 0.0665 - val_mse: 0.0665
Epoch 45/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1493 - mse: 0.1493
3021/3021 [==============================] - 0s 134us/sample - loss: 0.1633 - mse: 0.1633 - val_loss: 0.0657 - val_mse: 0.0657
Epoch 46/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1608 - mse: 0.1608
3021/3021 [==============================] - 0s 136us/sample - loss: 0.1662 - mse: 0.1662 - val_loss: 0.0626 - val_mse: 0.0626
Epoch 47/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1746 - mse: 0.1746
3021/3021 [==============================] - 1s 185us/sample - loss: 0.1689 - mse: 0.1689 - val_loss: 0.0635 - val_mse: 0.0635
Epoch 48/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1552 - mse: 0.1552
3021/3021 [==============================] - 0s 138us/sample - loss: 0.1645 - mse: 0.1645 - val_loss: 0.0618 - val_mse: 0.0618
Epoch 49/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1648 - mse: 0.1648
3021/3021 [==============================] - 0s 133us/sample - loss: 0.1650 - mse: 0.1650 - val_loss: 0.0568 - val_mse: 0.0568
Epoch 50/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1361 - mse: 0.1361
3021/3021 [==============================] - 0s 137us/sample - loss: 0.1530 - mse: 0.1530 - val_loss: 0.0555 - val_mse: 0.0555
Epoch 51/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1458 - mse: 0.1458
3021/3021 [==============================] - 0s 147us/sample - loss: 0.1623 - mse: 0.1623 - val_loss: 0.0562 - val_mse: 0.0562
Epoch 52/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1640 - mse: 0.1640
3021/3021 [==============================] - 0s 144us/sample - loss: 0.1631 - mse: 0.1631 - val_loss: 0.0550 - val_mse: 0.0550
Epoch 53/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1798 - mse: 0.1798
3021/3021 [==============================] - 0s 128us/sample - loss: 0.1633 - mse: 0.1633 - val_loss: 0.0546 - val_mse: 0.0546
Epoch 54/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1517 - mse: 0.1517
3021/3021 [==============================] - 0s 133us/sample - loss: 0.1601 - mse: 0.1601 - val_loss: 0.0550 - val_mse: 0.0550
Epoch 55/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1508 - mse: 0.1508
3021/3021 [==============================] - 0s 133us/sample - loss: 0.1540 - mse: 0.1540 - val_loss: 0.0502 - val_mse: 0.0502
Epoch 56/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1450 - mse: 0.1450
3021/3021 [==============================] - 0s 140us/sample - loss: 0.1562 - mse: 0.1562 - val_loss: 0.0489 - val_mse: 0.0489
Epoch 57/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1581 - mse: 0.1581
3021/3021 [==============================] - 0s 141us/sample - loss: 0.1483 - mse: 0.1483 - val_loss: 0.0483 - val_mse: 0.0483
Epoch 58/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1345 - mse: 0.1345
3021/3021 [==============================] - 0s 132us/sample - loss: 0.1483 - mse: 0.1483 - val_loss: 0.0481 - val_mse: 0.0481
Epoch 59/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1357 - mse: 0.1357
3021/3021 [==============================] - 0s 143us/sample - loss: 0.1495 - mse: 0.1495 - val_loss: 0.0490 - val_mse: 0.0490
Epoch 60/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1772 - mse: 0.1772
3021/3021 [==============================] - 0s 150us/sample - loss: 0.1564 - mse: 0.1564 - val_loss: 0.0488 - val_mse: 0.0488
Epoch 61/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1645 - mse: 0.1645
3021/3021 [==============================] - 0s 138us/sample - loss: 0.1599 - mse: 0.1599 - val_loss: 0.0467 - val_mse: 0.0467
Epoch 62/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1555 - mse: 0.1555
3021/3021 [==============================] - 0s 129us/sample - loss: 0.1471 - mse: 0.1471 - val_loss: 0.0462 - val_mse: 0.0462
Epoch 63/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1710 - mse: 0.1710
3021/3021 [==============================] - 0s 139us/sample - loss: 0.1563 - mse: 0.1563 - val_loss: 0.0460 - val_mse: 0.0460
Epoch 64/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1493 - mse: 0.1493
3021/3021 [==============================] - 0s 135us/sample - loss: 0.1559 - mse: 0.1559 - val_loss: 0.0470 - val_mse: 0.0470
Epoch 65/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1389 - mse: 0.1389
3021/3021 [==============================] - 0s 139us/sample - loss: 0.1491 - mse: 0.1491 - val_loss: 0.0460 - val_mse: 0.0460
Epoch 66/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1520 - mse: 0.1520
3021/3021 [==============================] - 0s 135us/sample - loss: 0.1462 - mse: 0.1462 - val_loss: 0.0456 - val_mse: 0.0456
Epoch 67/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1478 - mse: 0.1478
3021/3021 [==============================] - 0s 139us/sample - loss: 0.1532 - mse: 0.1532 - val_loss: 0.0458 - val_mse: 0.0458
Epoch 68/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1423 - mse: 0.1423
3021/3021 [==============================] - 0s 140us/sample - loss: 0.1512 - mse: 0.1512 - val_loss: 0.0453 - val_mse: 0.0453
Epoch 69/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1571 - mse: 0.1571
3021/3021 [==============================] - 0s 132us/sample - loss: 0.1497 - mse: 0.1497 - val_loss: 0.0453 - val_mse: 0.0453
Epoch 70/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1534 - mse: 0.1534
3021/3021 [==============================] - 0s 128us/sample - loss: 0.1511 - mse: 0.1511 - val_loss: 0.0452 - val_mse: 0.0452
Epoch 71/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1283 - mse: 0.1283
3021/3021 [==============================] - 0s 136us/sample - loss: 0.1476 - mse: 0.1476 - val_loss: 0.0435 - val_mse: 0.0435
Epoch 72/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1389 - mse: 0.1389
3021/3021 [==============================] - 0s 138us/sample - loss: 0.1478 - mse: 0.1478 - val_loss: 0.0441 - val_mse: 0.0441
Epoch 73/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1230 - mse: 0.1230
3021/3021 [==============================] - 0s 134us/sample - loss: 0.1464 - mse: 0.1464 - val_loss: 0.0426 - val_mse: 0.0426
Epoch 74/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1465 - mse: 0.1465
3021/3021 [==============================] - 0s 133us/sample - loss: 0.1498 - mse: 0.1498 - val_loss: 0.0460 - val_mse: 0.0460
Epoch 75/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1404 - mse: 0.1404
3021/3021 [==============================] - 0s 139us/sample - loss: 0.1513 - mse: 0.1513 - val_loss: 0.0436 - val_mse: 0.0436
Epoch 76/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1518 - mse: 0.1518
3021/3021 [==============================] - 0s 138us/sample - loss: 0.1391 - mse: 0.1391 - val_loss: 0.0430 - val_mse: 0.0430
Epoch 77/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1470 - mse: 0.1470
3021/3021 [==============================] - 0s 145us/sample - loss: 0.1576 - mse: 0.1576 - val_loss: 0.0438 - val_mse: 0.0438
Epoch 78/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1469 - mse: 0.1469
3021/3021 [==============================] - 0s 127us/sample - loss: 0.1479 - mse: 0.1479 - val_loss: 0.0432 - val_mse: 0.0432
Epoch 79/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1396 - mse: 0.1396
3021/3021 [==============================] - 0s 135us/sample - loss: 0.1429 - mse: 0.1429 - val_loss: 0.0456 - val_mse: 0.0456
Epoch 80/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1417 - mse: 0.1417
3021/3021 [==============================] - 0s 131us/sample - loss: 0.1528 - mse: 0.1528 - val_loss: 0.0410 - val_mse: 0.0410
Epoch 81/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1245 - mse: 0.1245
3021/3021 [==============================] - 0s 142us/sample - loss: 0.1465 - mse: 0.1465 - val_loss: 0.0416 - val_mse: 0.0416
Epoch 82/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1500 - mse: 0.1500
3021/3021 [==============================] - 0s 134us/sample - loss: 0.1506 - mse: 0.1506 - val_loss: 0.0409 - val_mse: 0.0409
Epoch 83/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1285 - mse: 0.1285
3021/3021 [==============================] - 0s 134us/sample - loss: 0.1363 - mse: 0.1363 - val_loss: 0.0405 - val_mse: 0.0405
Epoch 84/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1475 - mse: 0.1475
3021/3021 [==============================] - 0s 134us/sample - loss: 0.1411 - mse: 0.1411 - val_loss: 0.0401 - val_mse: 0.0401
Epoch 85/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1468 - mse: 0.1468
3021/3021 [==============================] - 0s 140us/sample - loss: 0.1431 - mse: 0.1431 - val_loss: 0.0402 - val_mse: 0.0402
Epoch 86/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1571 - mse: 0.1571
3021/3021 [==============================] - 0s 147us/sample - loss: 0.1422 - mse: 0.1422 - val_loss: 0.0420 - val_mse: 0.0420
Epoch 87/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1631 - mse: 0.1631
3021/3021 [==============================] - 0s 140us/sample - loss: 0.1459 - mse: 0.1459 - val_loss: 0.0424 - val_mse: 0.0424
Epoch 88/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1507 - mse: 0.1507
3021/3021 [==============================] - 0s 129us/sample - loss: 0.1453 - mse: 0.1453 - val_loss: 0.0417 - val_mse: 0.0417
Epoch 89/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1540 - mse: 0.1540
3021/3021 [==============================] - 0s 137us/sample - loss: 0.1411 - mse: 0.1411 - val_loss: 0.0430 - val_mse: 0.0430
Epoch 90/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1453 - mse: 0.1453
3021/3021 [==============================] - 0s 139us/sample - loss: 0.1384 - mse: 0.1384 - val_loss: 0.0436 - val_mse: 0.0436
Epoch 91/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1428 - mse: 0.1428
3021/3021 [==============================] - 0s 139us/sample - loss: 0.1462 - mse: 0.1462 - val_loss: 0.0420 - val_mse: 0.0420
Epoch 92/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1376 - mse: 0.1376
3021/3021 [==============================] - 0s 139us/sample - loss: 0.1405 - mse: 0.1405 - val_loss: 0.0435 - val_mse: 0.0435
Epoch 93/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1645 - mse: 0.1645
3021/3021 [==============================] - 0s 132us/sample - loss: 0.1399 - mse: 0.1399 - val_loss: 0.0424 - val_mse: 0.0424
Epoch 94/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1360 - mse: 0.1360
3021/3021 [==============================] - 0s 130us/sample - loss: 0.1408 - mse: 0.1408 - val_loss: 0.0444 - val_mse: 0.0444
Epoch 95/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1689 - mse: 0.1689
3021/3021 [==============================] - 0s 135us/sample - loss: 0.1449 - mse: 0.1449 - val_loss: 0.0439 - val_mse: 0.0439
Epoch 96/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1358 - mse: 0.1358
3021/3021 [==============================] - 0s 143us/sample - loss: 0.1375 - mse: 0.1375 - val_loss: 0.0442 - val_mse: 0.0442
Epoch 97/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1410 - mse: 0.1410
3021/3021 [==============================] - 0s 132us/sample - loss: 0.1372 - mse: 0.1372 - val_loss: 0.0432 - val_mse: 0.0432
Epoch 98/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1470 - mse: 0.1470
3021/3021 [==============================] - 0s 148us/sample - loss: 0.1400 - mse: 0.1400 - val_loss: 0.0410 - val_mse: 0.0410
Epoch 99/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1504 - mse: 0.1504
3021/3021 [==============================] - 0s 137us/sample - loss: 0.1407 - mse: 0.1407 - val_loss: 0.0377 - val_mse: 0.0377
Epoch 100/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.1475 - mse: 0.1475
3021/3021 [==============================] - 0s 131us/sample - loss: 0.1351 - mse: 0.1351 - val_loss: 0.0424 - val_mse: 0.0424Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-05-04T00-53-06Z
Training run 3/46 (flags = list(392, 392, 0.001, 100, 50, "relu", "tanh", 0.05, 0.05))
Using run directory runs/2020-05-04T00-53-52Z
> FLAGS <- flags(
+ flag_numeric("nodes1", 128),
+ flag_numeric("nodes2", 128),
+ flag_numeric("batch_size", 100),
+ flag_string("activation1" .... [TRUNCATED]
> model = keras_model_sequential()
> model %>%
+ layer_dense(units=FLAGS$nodes1, activation=FLAGS$activation1, input_shape=dim(efw_train2)[2]) %>%
+ layer_dropout(FLAGS$dropout1) %> .... [TRUNCATED]
> model %>% compile(
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ loss = 'mse',
+ metrics = c('mse')
+ )
> model %>% fit(
+ as.matrix(efw_train2), train2Label,
+ epochs=FLAGS$epochs,
+ batch_size=FLAGS$batch_size,
+ validation_data=list(as.matrix( .... [TRUNCATED]
Train on 3021 samples, validate on 334 samples
Epoch 1/50
100/3021 [..............................] - ETA: 7s - loss: 38.7251 - mse: 38.7251
1600/3021 [==============>...............] - ETA: 0s - loss: 28.4345 - mse: 28.4345
3021/3021 [==============================] - 1s 270us/sample - loss: 21.1719 - mse: 21.1719 - val_loss: 9.2258 - val_mse: 9.2258
Epoch 2/50
100/3021 [..............................] - ETA: 0s - loss: 8.4923 - mse: 8.4923
1400/3021 [============>.................] - ETA: 0s - loss: 7.8103 - mse: 7.8103
3021/3021 [==============================] - 1s 167us/sample - loss: 6.1511 - mse: 6.1511 - val_loss: 3.4023 - val_mse: 3.4023
Epoch 3/50
100/3021 [..............................] - ETA: 0s - loss: 3.6245 - mse: 3.6245
1600/3021 [==============>...............] - ETA: 0s - loss: 2.7286 - mse: 2.7286
2900/3021 [===========================>..] - ETA: 0s - loss: 2.3367 - mse: 2.3367
3021/3021 [==============================] - 1s 175us/sample - loss: 2.3059 - mse: 2.3059 - val_loss: 1.4200 - val_mse: 1.4200
Epoch 4/50
100/3021 [..............................] - ETA: 0s - loss: 1.1511 - mse: 1.1511
1400/3021 [============>.................] - ETA: 0s - loss: 1.2487 - mse: 1.2487
3021/3021 [==============================] - 0s 163us/sample - loss: 1.0259 - mse: 1.0259 - val_loss: 0.7652 - val_mse: 0.7652
Epoch 5/50
100/3021 [..............................] - ETA: 0s - loss: 0.5434 - mse: 0.5434
1800/3021 [================>.............] - ETA: 0s - loss: 0.5968 - mse: 0.5968
3021/3021 [==============================] - 1s 188us/sample - loss: 0.5536 - mse: 0.5536 - val_loss: 0.4959 - val_mse: 0.4959
Epoch 6/50
100/3021 [..............................] - ETA: 0s - loss: 0.4419 - mse: 0.4419
1600/3021 [==============>...............] - ETA: 0s - loss: 0.4076 - mse: 0.4076
3021/3021 [==============================] - 1s 167us/sample - loss: 0.3675 - mse: 0.3675 - val_loss: 0.3596 - val_mse: 0.3596
Epoch 7/50
100/3021 [..............................] - ETA: 0s - loss: 0.3112 - mse: 0.3112
1900/3021 [=================>............] - ETA: 0s - loss: 0.2880 - mse: 0.2880
3021/3021 [==============================] - 1s 172us/sample - loss: 0.2792 - mse: 0.2792 - val_loss: 0.2950 - val_mse: 0.2950
Epoch 8/50
100/3021 [..............................] - ETA: 0s - loss: 0.3036 - mse: 0.3036
1200/3021 [==========>...................] - ETA: 0s - loss: 0.2406 - mse: 0.2406
3000/3021 [============================>.] - ETA: 0s - loss: 0.2239 - mse: 0.2239
3021/3021 [==============================] - 1s 175us/sample - loss: 0.2234 - mse: 0.2234 - val_loss: 0.2469 - val_mse: 0.2469
Epoch 9/50
100/3021 [..............................] - ETA: 0s - loss: 0.1716 - mse: 0.1716
1600/3021 [==============>...............] - ETA: 0s - loss: 0.1907 - mse: 0.1907
3021/3021 [==============================] - 1s 172us/sample - loss: 0.1886 - mse: 0.1886 - val_loss: 0.2115 - val_mse: 0.2115
Epoch 10/50
100/3021 [..............................] - ETA: 0s - loss: 0.1864 - mse: 0.1864
1600/3021 [==============>...............] - ETA: 0s - loss: 0.1585 - mse: 0.1585
3021/3021 [==============================] - 1s 166us/sample - loss: 0.1529 - mse: 0.1529 - val_loss: 0.1870 - val_mse: 0.1870
Epoch 11/50
100/3021 [..............................] - ETA: 0s - loss: 0.1083 - mse: 0.1083
1700/3021 [===============>..............] - ETA: 0s - loss: 0.1278 - mse: 0.1278
3021/3021 [==============================] - 1s 169us/sample - loss: 0.1287 - mse: 0.1287 - val_loss: 0.1675 - val_mse: 0.1675
Epoch 12/50
100/3021 [..............................] - ETA: 0s - loss: 0.0931 - mse: 0.0931
1800/3021 [================>.............] - ETA: 0s - loss: 0.1160 - mse: 0.1160
3021/3021 [==============================] - 1s 167us/sample - loss: 0.1217 - mse: 0.1217 - val_loss: 0.1537 - val_mse: 0.1537
Epoch 13/50
100/3021 [..............................] - ETA: 0s - loss: 0.0979 - mse: 0.0979
1300/3021 [===========>..................] - ETA: 0s - loss: 0.1024 - mse: 0.1024
2800/3021 [==========================>...] - ETA: 0s - loss: 0.1057 - mse: 0.1057
3021/3021 [==============================] - 1s 172us/sample - loss: 0.1055 - mse: 0.1055 - val_loss: 0.1431 - val_mse: 0.1431
Epoch 14/50
100/3021 [..............................] - ETA: 0s - loss: 0.0892 - mse: 0.0892
1800/3021 [================>.............] - ETA: 0s - loss: 0.1011 - mse: 0.1011
3021/3021 [==============================] - 1s 167us/sample - loss: 0.0992 - mse: 0.0992 - val_loss: 0.1323 - val_mse: 0.1323
Epoch 15/50
100/3021 [..............................] - ETA: 0s - loss: 0.0875 - mse: 0.0875
1800/3021 [================>.............] - ETA: 0s - loss: 0.0920 - mse: 0.0920
3021/3021 [==============================] - 1s 171us/sample - loss: 0.0905 - mse: 0.0905 - val_loss: 0.1206 - val_mse: 0.1206
Epoch 16/50
100/3021 [..............................] - ETA: 0s - loss: 0.0705 - mse: 0.0705
1600/3021 [==============>...............] - ETA: 0s - loss: 0.0786 - mse: 0.0786
3021/3021 [==============================] - 1s 166us/sample - loss: 0.0817 - mse: 0.0817 - val_loss: 0.1138 - val_mse: 0.1138
Epoch 17/50
100/3021 [..............................] - ETA: 0s - loss: 0.0787 - mse: 0.0787
1800/3021 [================>.............] - ETA: 0s - loss: 0.0796 - mse: 0.0796
3021/3021 [==============================] - 1s 166us/sample - loss: 0.0815 - mse: 0.0815 - val_loss: 0.1072 - val_mse: 0.1072
Epoch 18/50
100/3021 [..............................] - ETA: 0s - loss: 0.0644 - mse: 0.0644
1400/3021 [============>.................] - ETA: 0s - loss: 0.0762 - mse: 0.0762
3000/3021 [============================>.] - ETA: 0s - loss: 0.0740 - mse: 0.0740
3021/3021 [==============================] - 1s 181us/sample - loss: 0.0739 - mse: 0.0739 - val_loss: 0.1010 - val_mse: 0.1010
Epoch 19/50
100/3021 [..............................] - ETA: 0s - loss: 0.0697 - mse: 0.0697
1400/3021 [============>.................] - ETA: 0s - loss: 0.0661 - mse: 0.0661
3000/3021 [============================>.] - ETA: 0s - loss: 0.0695 - mse: 0.0695
3021/3021 [==============================] - 1s 177us/sample - loss: 0.0693 - mse: 0.0693 - val_loss: 0.0952 - val_mse: 0.0952
Epoch 20/50
100/3021 [..............................] - ETA: 0s - loss: 0.0495 - mse: 0.0495
900/3021 [=======>......................] - ETA: 0s - loss: 0.0629 - mse: 0.0629
2600/3021 [========================>.....] - ETA: 0s - loss: 0.0631 - mse: 0.0631
3021/3021 [==============================] - 1s 185us/sample - loss: 0.0626 - mse: 0.0626 - val_loss: 0.0960 - val_mse: 0.0960
Epoch 21/50
100/3021 [..............................] - ETA: 0s - loss: 0.0521 - mse: 0.0521
1700/3021 [===============>..............] - ETA: 0s - loss: 0.0605 - mse: 0.0605
3021/3021 [==============================] - 1s 166us/sample - loss: 0.0606 - mse: 0.0606 - val_loss: 0.0963 - val_mse: 0.0963
Epoch 22/50
100/3021 [..............................] - ETA: 0s - loss: 0.0570 - mse: 0.0570
1600/3021 [==============>...............] - ETA: 0s - loss: 0.0627 - mse: 0.0627
3021/3021 [==============================] - 1s 169us/sample - loss: 0.0592 - mse: 0.0592 - val_loss: 0.0918 - val_mse: 0.0918
Epoch 23/50
100/3021 [..............................] - ETA: 0s - loss: 0.0875 - mse: 0.0875
1500/3021 [=============>................] - ETA: 0s - loss: 0.0595 - mse: 0.0595
3000/3021 [============================>.] - ETA: 0s - loss: 0.0581 - mse: 0.0581
3021/3021 [==============================] - 1s 167us/sample - loss: 0.0581 - mse: 0.0581 - val_loss: 0.0943 - val_mse: 0.0943
Epoch 24/50
100/3021 [..............................] - ETA: 0s - loss: 0.0493 - mse: 0.0493
1700/3021 [===============>..............] - ETA: 0s - loss: 0.0544 - mse: 0.0544
3021/3021 [==============================] - 1s 184us/sample - loss: 0.0548 - mse: 0.0548 - val_loss: 0.0849 - val_mse: 0.0849
Epoch 25/50
100/3021 [..............................] - ETA: 0s - loss: 0.0405 - mse: 0.0405
1800/3021 [================>.............] - ETA: 0s - loss: 0.0511 - mse: 0.0511
3021/3021 [==============================] - 0s 164us/sample - loss: 0.0520 - mse: 0.0520 - val_loss: 0.0852 - val_mse: 0.0852
Epoch 26/50
100/3021 [..............................] - ETA: 0s - loss: 0.0367 - mse: 0.0367
1400/3021 [============>.................] - ETA: 0s - loss: 0.0489 - mse: 0.0489
2600/3021 [========================>.....] - ETA: 0s - loss: 0.0499 - mse: 0.0499
3021/3021 [==============================] - 1s 187us/sample - loss: 0.0500 - mse: 0.0500 - val_loss: 0.0834 - val_mse: 0.0834
Epoch 27/50
100/3021 [..............................] - ETA: 0s - loss: 0.0508 - mse: 0.0508
1300/3021 [===========>..................] - ETA: 0s - loss: 0.0524 - mse: 0.0524
3000/3021 [============================>.] - ETA: 0s - loss: 0.0509 - mse: 0.0509
3021/3021 [==============================] - 1s 170us/sample - loss: 0.0509 - mse: 0.0509 - val_loss: 0.0885 - val_mse: 0.0885
Epoch 28/50
100/3021 [..............................] - ETA: 0s - loss: 0.0470 - mse: 0.0470
1700/3021 [===============>..............] - ETA: 0s - loss: 0.0504 - mse: 0.0504
3021/3021 [==============================] - 1s 170us/sample - loss: 0.0498 - mse: 0.0498 - val_loss: 0.0824 - val_mse: 0.0824
Epoch 29/50
100/3021 [..............................] - ETA: 0s - loss: 0.0642 - mse: 0.0642
1800/3021 [================>.............] - ETA: 0s - loss: 0.0520 - mse: 0.0520
3021/3021 [==============================] - 1s 166us/sample - loss: 0.0497 - mse: 0.0497 - val_loss: 0.0789 - val_mse: 0.0789
Epoch 30/50
100/3021 [..............................] - ETA: 0s - loss: 0.0377 - mse: 0.0377
1700/3021 [===============>..............] - ETA: 0s - loss: 0.0453 - mse: 0.0453
3021/3021 [==============================] - 1s 174us/sample - loss: 0.0452 - mse: 0.0452 - val_loss: 0.0756 - val_mse: 0.0756
Epoch 31/50
100/3021 [..............................] - ETA: 0s - loss: 0.0375 - mse: 0.0375
1600/3021 [==============>...............] - ETA: 0s - loss: 0.0448 - mse: 0.0448
3021/3021 [==============================] - 1s 173us/sample - loss: 0.0441 - mse: 0.0441 - val_loss: 0.0769 - val_mse: 0.0769
Epoch 32/50
100/3021 [..............................] - ETA: 0s - loss: 0.0329 - mse: 0.0329
1800/3021 [================>.............] - ETA: 0s - loss: 0.0431 - mse: 0.0431
3021/3021 [==============================] - 1s 168us/sample - loss: 0.0435 - mse: 0.0435 - val_loss: 0.0725 - val_mse: 0.0725
Epoch 33/50
100/3021 [..............................] - ETA: 0s - loss: 0.0385 - mse: 0.0385
1500/3021 [=============>................] - ETA: 0s - loss: 0.0425 - mse: 0.0425
3021/3021 [==============================] - 1s 170us/sample - loss: 0.0430 - mse: 0.0430 - val_loss: 0.0731 - val_mse: 0.0731
Epoch 34/50
100/3021 [..............................] - ETA: 0s - loss: 0.0400 - mse: 0.0400
1700/3021 [===============>..............] - ETA: 0s - loss: 0.0429 - mse: 0.0429
3021/3021 [==============================] - 1s 169us/sample - loss: 0.0441 - mse: 0.0441 - val_loss: 0.0727 - val_mse: 0.0727
Epoch 35/50
100/3021 [..............................] - ETA: 0s - loss: 0.0396 - mse: 0.0396
1700/3021 [===============>..............] - ETA: 0s - loss: 0.0392 - mse: 0.0392
3021/3021 [==============================] - 1s 174us/sample - loss: 0.0396 - mse: 0.0396 - val_loss: 0.0722 - val_mse: 0.0722
Epoch 36/50
100/3021 [..............................] - ETA: 0s - loss: 0.0508 - mse: 0.0508
1600/3021 [==============>...............] - ETA: 0s - loss: 0.0421 - mse: 0.0421
3021/3021 [==============================] - 1s 184us/sample - loss: 0.0435 - mse: 0.0435 - val_loss: 0.0701 - val_mse: 0.0701
Epoch 37/50
100/3021 [..............................] - ETA: 0s - loss: 0.0329 - mse: 0.0329
1600/3021 [==============>...............] - ETA: 0s - loss: 0.0415 - mse: 0.0415
3021/3021 [==============================] - 1s 196us/sample - loss: 0.0408 - mse: 0.0408 - val_loss: 0.0711 - val_mse: 0.0711
Epoch 38/50
100/3021 [..............................] - ETA: 0s - loss: 0.0440 - mse: 0.0440
1000/3021 [========>.....................] - ETA: 0s - loss: 0.0400 - mse: 0.0400
2600/3021 [========================>.....] - ETA: 0s - loss: 0.0399 - mse: 0.0399
3021/3021 [==============================] - 1s 179us/sample - loss: 0.0392 - mse: 0.0392 - val_loss: 0.0707 - val_mse: 0.0707
Epoch 39/50
100/3021 [..............................] - ETA: 0s - loss: 0.0467 - mse: 0.0467
1600/3021 [==============>...............] - ETA: 0s - loss: 0.0380 - mse: 0.0380
3021/3021 [==============================] - 1s 194us/sample - loss: 0.0378 - mse: 0.0378 - val_loss: 0.0674 - val_mse: 0.0674
Epoch 40/50
100/3021 [..............................] - ETA: 0s - loss: 0.0344 - mse: 0.0344
1700/3021 [===============>..............] - ETA: 0s - loss: 0.0365 - mse: 0.0365
3021/3021 [==============================] - 0s 165us/sample - loss: 0.0376 - mse: 0.0376 - val_loss: 0.0694 - val_mse: 0.0694
Epoch 41/50
100/3021 [..............................] - ETA: 0s - loss: 0.0334 - mse: 0.0334
1700/3021 [===============>..............] - ETA: 0s - loss: 0.0341 - mse: 0.0341
3021/3021 [==============================] - 1s 169us/sample - loss: 0.0355 - mse: 0.0355 - val_loss: 0.0656 - val_mse: 0.0656
Epoch 42/50
100/3021 [..............................] - ETA: 0s - loss: 0.0353 - mse: 0.0353
1700/3021 [===============>..............] - ETA: 0s - loss: 0.0349 - mse: 0.0349
3021/3021 [==============================] - 0s 165us/sample - loss: 0.0358 - mse: 0.0358 - val_loss: 0.0625 - val_mse: 0.0625
Epoch 43/50
100/3021 [..............................] - ETA: 0s - loss: 0.0409 - mse: 0.0409
1400/3021 [============>.................] - ETA: 0s - loss: 0.0344 - mse: 0.0344
2900/3021 [===========================>..] - ETA: 0s - loss: 0.0366 - mse: 0.0366
3021/3021 [==============================] - 1s 178us/sample - loss: 0.0366 - mse: 0.0366 - val_loss: 0.0653 - val_mse: 0.0653
Epoch 44/50
100/3021 [..............................] - ETA: 0s - loss: 0.0325 - mse: 0.0325
1700/3021 [===============>..............] - ETA: 0s - loss: 0.0374 - mse: 0.0374
3021/3021 [==============================] - 0s 165us/sample - loss: 0.0371 - mse: 0.0371 - val_loss: 0.0639 - val_mse: 0.0639
Epoch 45/50
100/3021 [..............................] - ETA: 0s - loss: 0.0301 - mse: 0.0301
1700/3021 [===============>..............] - ETA: 0s - loss: 0.0323 - mse: 0.0323
3021/3021 [==============================] - 1s 180us/sample - loss: 0.0342 - mse: 0.0342 - val_loss: 0.0630 - val_mse: 0.0630
Epoch 46/50
100/3021 [..............................] - ETA: 0s - loss: 0.0310 - mse: 0.0310
1800/3021 [================>.............] - ETA: 0s - loss: 0.0348 - mse: 0.0348
3021/3021 [==============================] - 1s 166us/sample - loss: 0.0343 - mse: 0.0343 - val_loss: 0.0653 - val_mse: 0.0653
Epoch 47/50
100/3021 [..............................] - ETA: 0s - loss: 0.0364 - mse: 0.0364
1800/3021 [================>.............] - ETA: 0s - loss: 0.0361 - mse: 0.0361
3021/3021 [==============================] - 1s 166us/sample - loss: 0.0357 - mse: 0.0357 - val_loss: 0.0616 - val_mse: 0.0616
Epoch 48/50
100/3021 [..............................] - ETA: 0s - loss: 0.0334 - mse: 0.0334
1500/3021 [=============>................] - ETA: 0s - loss: 0.0311 - mse: 0.0311
3000/3021 [============================>.] - ETA: 0s - loss: 0.0335 - mse: 0.0335
3021/3021 [==============================] - 1s 172us/sample - loss: 0.0335 - mse: 0.0335 - val_loss: 0.0633 - val_mse: 0.0633
Epoch 49/50
100/3021 [..............................] - ETA: 0s - loss: 0.0303 - mse: 0.0303
1800/3021 [================>.............] - ETA: 0s - loss: 0.0345 - mse: 0.0345
3021/3021 [==============================] - 1s 170us/sample - loss: 0.0340 - mse: 0.0340 - val_loss: 0.0636 - val_mse: 0.0636
Epoch 50/50
100/3021 [..............................] - ETA: 0s - loss: 0.0326 - mse: 0.0326
1000/3021 [========>.....................] - ETA: 0s - loss: 0.0351 - mse: 0.0351
2800/3021 [==========================>...] - ETA: 0s - loss: 0.0349 - mse: 0.0349
3021/3021 [==============================] - 1s 172us/sample - loss: 0.0347 - mse: 0.0347 - val_loss: 0.0583 - val_mse: 0.0583Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-05-04T00-53-52Z
Training run 4/46 (flags = list(128, 392, 0.001, 500, 30, "relu", "tanh", 0.1, 0.5))
Using run directory runs/2020-05-04T00-54-22Z
> FLAGS <- flags(
+ flag_numeric("nodes1", 128),
+ flag_numeric("nodes2", 128),
+ flag_numeric("batch_size", 100),
+ flag_string("activation1" .... [TRUNCATED]
> model = keras_model_sequential()
> model %>%
+ layer_dense(units=FLAGS$nodes1, activation=FLAGS$activation1, input_shape=dim(efw_train2)[2]) %>%
+ layer_dropout(FLAGS$dropout1) %> .... [TRUNCATED]
> model %>% compile(
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ loss = 'mse',
+ metrics = c('mse')
+ )
> model %>% fit(
+ as.matrix(efw_train2), train2Label,
+ epochs=FLAGS$epochs,
+ batch_size=FLAGS$batch_size,
+ validation_data=list(as.matrix( .... [TRUNCATED]
Train on 3021 samples, validate on 334 samples
Epoch 1/30
500/3021 [===>..........................] - ETA: 1s - loss: 43.3573 - mse: 43.3573
3021/3021 [==============================] - 1s 239us/sample - loss: 40.8583 - mse: 40.8583 - val_loss: 36.5476 - val_mse: 36.5476
Epoch 2/30
500/3021 [===>..........................] - ETA: 0s - loss: 35.6755 - mse: 35.6755
3021/3021 [==============================] - 0s 146us/sample - loss: 33.9957 - mse: 33.9957 - val_loss: 30.2388 - val_mse: 30.2388
Epoch 3/30
500/3021 [===>..........................] - ETA: 0s - loss: 30.3894 - mse: 30.3894
3021/3021 [==============================] - 0s 142us/sample - loss: 28.0519 - mse: 28.0519 - val_loss: 24.6778 - val_mse: 24.6778
Epoch 4/30
500/3021 [===>..........................] - ETA: 0s - loss: 24.5593 - mse: 24.5593
3021/3021 [==============================] - 0s 133us/sample - loss: 22.8150 - mse: 22.8150 - val_loss: 19.8703 - val_mse: 19.8703
Epoch 5/30
500/3021 [===>..........................] - ETA: 0s - loss: 20.1997 - mse: 20.1997
3021/3021 [==============================] - 0s 143us/sample - loss: 18.3541 - mse: 18.3541 - val_loss: 15.9303 - val_mse: 15.9303
Epoch 6/30
500/3021 [===>..........................] - ETA: 0s - loss: 15.1821 - mse: 15.1821
3021/3021 [==============================] - 0s 144us/sample - loss: 14.7509 - mse: 14.7509 - val_loss: 12.9528 - val_mse: 12.9528
Epoch 7/30
500/3021 [===>..........................] - ETA: 0s - loss: 12.7940 - mse: 12.7940
3021/3021 [==============================] - 0s 136us/sample - loss: 12.1770 - mse: 12.1770 - val_loss: 10.8096 - val_mse: 10.8096
Epoch 8/30
500/3021 [===>..........................] - ETA: 0s - loss: 11.2086 - mse: 11.2086
3021/3021 [==============================] - 0s 136us/sample - loss: 10.3031 - mse: 10.3031 - val_loss: 9.3112 - val_mse: 9.3112
Epoch 9/30
500/3021 [===>..........................] - ETA: 0s - loss: 9.3934 - mse: 9.3934
3021/3021 [==============================] - 0s 137us/sample - loss: 8.9344 - mse: 8.9344 - val_loss: 8.1388 - val_mse: 8.1388
Epoch 10/30
500/3021 [===>..........................] - ETA: 0s - loss: 8.1180 - mse: 8.1180
3021/3021 [==============================] - 0s 148us/sample - loss: 7.8760 - mse: 7.8760 - val_loss: 7.1519 - val_mse: 7.1519
Epoch 11/30
500/3021 [===>..........................] - ETA: 0s - loss: 7.3367 - mse: 7.3367
3021/3021 [==============================] - 0s 135us/sample - loss: 6.9798 - mse: 6.9798 - val_loss: 6.2583 - val_mse: 6.2583
Epoch 12/30
500/3021 [===>..........................] - ETA: 0s - loss: 6.5766 - mse: 6.5766
3021/3021 [==============================] - 0s 129us/sample - loss: 6.1278 - mse: 6.1278 - val_loss: 5.4748 - val_mse: 5.4748
Epoch 13/30
500/3021 [===>..........................] - ETA: 0s - loss: 5.8792 - mse: 5.8792
3021/3021 [==============================] - 0s 140us/sample - loss: 5.3822 - mse: 5.3822 - val_loss: 4.7831 - val_mse: 4.7831
Epoch 14/30
500/3021 [===>..........................] - ETA: 0s - loss: 5.2421 - mse: 5.2421
3021/3021 [==============================] - 0s 137us/sample - loss: 4.6931 - mse: 4.6931 - val_loss: 4.1751 - val_mse: 4.1751
Epoch 15/30
500/3021 [===>..........................] - ETA: 0s - loss: 4.2820 - mse: 4.2820
3021/3021 [==============================] - 0s 137us/sample - loss: 4.1399 - mse: 4.1399 - val_loss: 3.6405 - val_mse: 3.6405
Epoch 16/30
500/3021 [===>..........................] - ETA: 0s - loss: 3.6183 - mse: 3.6183
3021/3021 [==============================] - 0s 141us/sample - loss: 3.6260 - mse: 3.6260 - val_loss: 3.1850 - val_mse: 3.1850
Epoch 17/30
500/3021 [===>..........................] - ETA: 0s - loss: 3.0114 - mse: 3.0114
3021/3021 [==============================] - 0s 140us/sample - loss: 3.1468 - mse: 3.1468 - val_loss: 2.7817 - val_mse: 2.7817
Epoch 18/30
500/3021 [===>..........................] - ETA: 0s - loss: 2.9554 - mse: 2.9554
3021/3021 [==============================] - 0s 140us/sample - loss: 2.7233 - mse: 2.7233 - val_loss: 2.4510 - val_mse: 2.4510
Epoch 19/30
500/3021 [===>..........................] - ETA: 0s - loss: 2.5674 - mse: 2.5674
3021/3021 [==============================] - 0s 145us/sample - loss: 2.4151 - mse: 2.4151 - val_loss: 2.1556 - val_mse: 2.1556
Epoch 20/30
500/3021 [===>..........................] - ETA: 0s - loss: 2.3744 - mse: 2.3744
3021/3021 [==============================] - 0s 153us/sample - loss: 2.1519 - mse: 2.1519 - val_loss: 1.8851 - val_mse: 1.8851
Epoch 21/30
500/3021 [===>..........................] - ETA: 0s - loss: 1.9920 - mse: 1.9920
3021/3021 [==============================] - 0s 142us/sample - loss: 1.8780 - mse: 1.8780 - val_loss: 1.6719 - val_mse: 1.6719
Epoch 22/30
500/3021 [===>..........................] - ETA: 0s - loss: 1.8170 - mse: 1.8170
3021/3021 [==============================] - 0s 143us/sample - loss: 1.7030 - mse: 1.7030 - val_loss: 1.4909 - val_mse: 1.4909
Epoch 23/30
500/3021 [===>..........................] - ETA: 0s - loss: 1.4331 - mse: 1.4331
3021/3021 [==============================] - 0s 142us/sample - loss: 1.4879 - mse: 1.4879 - val_loss: 1.3226 - val_mse: 1.3226
Epoch 24/30
500/3021 [===>..........................] - ETA: 0s - loss: 1.3693 - mse: 1.3693
3021/3021 [==============================] - 0s 138us/sample - loss: 1.3387 - mse: 1.3387 - val_loss: 1.1808 - val_mse: 1.1808
Epoch 25/30
500/3021 [===>..........................] - ETA: 0s - loss: 1.2713 - mse: 1.2713
3021/3021 [==============================] - 0s 133us/sample - loss: 1.2141 - mse: 1.2141 - val_loss: 1.0637 - val_mse: 1.0637
Epoch 26/30
500/3021 [===>..........................] - ETA: 0s - loss: 1.2090 - mse: 1.2090
3021/3021 [==============================] - 0s 136us/sample - loss: 1.1177 - mse: 1.1177 - val_loss: 0.9666 - val_mse: 0.9666
Epoch 27/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.9687 - mse: 0.9687
3021/3021 [==============================] - 0s 132us/sample - loss: 1.0049 - mse: 1.0049 - val_loss: 0.8905 - val_mse: 0.8905
Epoch 28/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.9279 - mse: 0.9279
3021/3021 [==============================] - 0s 135us/sample - loss: 0.9344 - mse: 0.9344 - val_loss: 0.8095 - val_mse: 0.8095
Epoch 29/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.8714 - mse: 0.8714
3021/3021 [==============================] - 0s 134us/sample - loss: 0.8394 - mse: 0.8394 - val_loss: 0.7427 - val_mse: 0.7427
Epoch 30/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.7436 - mse: 0.7436
3021/3021 [==============================] - 0s 139us/sample - loss: 0.8041 - mse: 0.8041 - val_loss: 0.6909 - val_mse: 0.6909Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-05-04T00-54-22Z
Training run 5/46 (flags = list(392, 128, 0.01, 500, 30, "sigmoid", "tanh", 0.2, 0.05))
Using run directory runs/2020-05-04T00-54-38Z
> FLAGS <- flags(
+ flag_numeric("nodes1", 128),
+ flag_numeric("nodes2", 128),
+ flag_numeric("batch_size", 100),
+ flag_string("activation1" .... [TRUNCATED]
> model = keras_model_sequential()
> model %>%
+ layer_dense(units=FLAGS$nodes1, activation=FLAGS$activation1, input_shape=dim(efw_train2)[2]) %>%
+ layer_dropout(FLAGS$dropout1) %> .... [TRUNCATED]
> model %>% compile(
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ loss = 'mse',
+ metrics = c('mse')
+ )
> model %>% fit(
+ as.matrix(efw_train2), train2Label,
+ epochs=FLAGS$epochs,
+ batch_size=FLAGS$batch_size,
+ validation_data=list(as.matrix( .... [TRUNCATED]
Train on 3021 samples, validate on 334 samples
Epoch 1/30
500/3021 [===>..........................] - ETA: 1s - loss: 28.0103 - mse: 28.0103
3021/3021 [==============================] - 1s 246us/sample - loss: 8.9554 - mse: 8.9554 - val_loss: 6.4838 - val_mse: 6.4838
Epoch 2/30
500/3021 [===>..........................] - ETA: 0s - loss: 6.7005 - mse: 6.7005
3021/3021 [==============================] - 0s 156us/sample - loss: 2.5363 - mse: 2.5363 - val_loss: 3.2251 - val_mse: 3.2251
Epoch 3/30
500/3021 [===>..........................] - ETA: 0s - loss: 3.1313 - mse: 3.1313
3021/3021 [==============================] - 0s 151us/sample - loss: 2.0042 - mse: 2.0042 - val_loss: 0.5147 - val_mse: 0.5147
Epoch 4/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.6706 - mse: 0.6706
3021/3021 [==============================] - 0s 150us/sample - loss: 1.0976 - mse: 1.0976 - val_loss: 0.1130 - val_mse: 0.1130
Epoch 5/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.2786 - mse: 0.2786
3021/3021 [==============================] - 0s 148us/sample - loss: 0.4721 - mse: 0.4721 - val_loss: 0.2802 - val_mse: 0.2802
Epoch 6/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.3735 - mse: 0.3735
3021/3021 [==============================] - 0s 143us/sample - loss: 0.2977 - mse: 0.2977 - val_loss: 0.2220 - val_mse: 0.2220
Epoch 7/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.3744 - mse: 0.3744
3021/3021 [==============================] - 0s 142us/sample - loss: 0.2601 - mse: 0.2601 - val_loss: 0.1701 - val_mse: 0.1701
Epoch 8/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.2919 - mse: 0.2919
3021/3021 [==============================] - 0s 146us/sample - loss: 0.2322 - mse: 0.2322 - val_loss: 0.1121 - val_mse: 0.1121
Epoch 9/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.2311 - mse: 0.2311
3021/3021 [==============================] - 0s 144us/sample - loss: 0.2119 - mse: 0.2119 - val_loss: 0.0787 - val_mse: 0.0787
Epoch 10/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.1950 - mse: 0.1950
3021/3021 [==============================] - 0s 158us/sample - loss: 0.1984 - mse: 0.1984 - val_loss: 0.0677 - val_mse: 0.0677
Epoch 11/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.1859 - mse: 0.1859
3021/3021 [==============================] - 0s 147us/sample - loss: 0.1807 - mse: 0.1807 - val_loss: 0.0514 - val_mse: 0.0514
Epoch 12/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.1937 - mse: 0.1937
3021/3021 [==============================] - 0s 147us/sample - loss: 0.1636 - mse: 0.1636 - val_loss: 0.0508 - val_mse: 0.0508
Epoch 13/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.1444 - mse: 0.1444
3021/3021 [==============================] - 0s 144us/sample - loss: 0.1624 - mse: 0.1624 - val_loss: 0.0539 - val_mse: 0.0539
Epoch 14/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.1756 - mse: 0.1756
3021/3021 [==============================] - 0s 163us/sample - loss: 0.1669 - mse: 0.1669 - val_loss: 0.0457 - val_mse: 0.0457
Epoch 15/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.1315 - mse: 0.1315
3021/3021 [==============================] - 0s 148us/sample - loss: 0.1525 - mse: 0.1525 - val_loss: 0.0496 - val_mse: 0.0496
Epoch 16/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.1618 - mse: 0.1618
3021/3021 [==============================] - 0s 143us/sample - loss: 0.1570 - mse: 0.1570 - val_loss: 0.0631 - val_mse: 0.0631
Epoch 17/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.1820 - mse: 0.1820
3021/3021 [==============================] - 0s 146us/sample - loss: 0.1674 - mse: 0.1674 - val_loss: 0.0570 - val_mse: 0.0570
Epoch 18/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.1308 - mse: 0.1308
3021/3021 [==============================] - 0s 143us/sample - loss: 0.1586 - mse: 0.1586 - val_loss: 0.0485 - val_mse: 0.0485
Epoch 19/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.1596 - mse: 0.1596
3021/3021 [==============================] - 0s 154us/sample - loss: 0.1543 - mse: 0.1543 - val_loss: 0.0497 - val_mse: 0.0497
Epoch 20/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.1542 - mse: 0.1542
3021/3021 [==============================] - 0s 154us/sample - loss: 0.1534 - mse: 0.1534 - val_loss: 0.0464 - val_mse: 0.0464
Epoch 21/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.1270 - mse: 0.1270
3021/3021 [==============================] - 0s 152us/sample - loss: 0.1370 - mse: 0.1370 - val_loss: 0.0450 - val_mse: 0.0450
Epoch 22/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.1416 - mse: 0.1416
3021/3021 [==============================] - 0s 144us/sample - loss: 0.1389 - mse: 0.1389 - val_loss: 0.0411 - val_mse: 0.0411
Epoch 23/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.1414 - mse: 0.1414
3021/3021 [==============================] - 0s 148us/sample - loss: 0.1325 - mse: 0.1325 - val_loss: 0.0451 - val_mse: 0.0451
Epoch 24/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.1391 - mse: 0.1391
3021/3021 [==============================] - 1s 173us/sample - loss: 0.1460 - mse: 0.1460 - val_loss: 0.0584 - val_mse: 0.0584
Epoch 25/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.1545 - mse: 0.1545
3021/3021 [==============================] - 0s 147us/sample - loss: 0.1459 - mse: 0.1459 - val_loss: 0.0515 - val_mse: 0.0515
Epoch 26/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.1428 - mse: 0.1428
3021/3021 [==============================] - 0s 146us/sample - loss: 0.1364 - mse: 0.1364 - val_loss: 0.0554 - val_mse: 0.0554
Epoch 27/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.1409 - mse: 0.1409
3021/3021 [==============================] - 0s 148us/sample - loss: 0.1390 - mse: 0.1390 - val_loss: 0.0505 - val_mse: 0.0505
Epoch 28/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.1513 - mse: 0.1513
3021/3021 [==============================] - 0s 143us/sample - loss: 0.1342 - mse: 0.1342 - val_loss: 0.0467 - val_mse: 0.0467
Epoch 29/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.1472 - mse: 0.1472
3021/3021 [==============================] - 0s 143us/sample - loss: 0.1283 - mse: 0.1283 - val_loss: 0.0449 - val_mse: 0.0449
Epoch 30/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.1188 - mse: 0.1188
3021/3021 [==============================] - 0s 155us/sample - loss: 0.1246 - mse: 0.1246 - val_loss: 0.0478 - val_mse: 0.0478Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-05-04T00-54-38Z
Training run 6/46 (flags = list(128, 128, 1e-04, 100, 50, "relu", "tanh", 0.5, 0.5))
Using run directory runs/2020-05-04T00-54-55Z
> FLAGS <- flags(
+ flag_numeric("nodes1", 128),
+ flag_numeric("nodes2", 128),
+ flag_numeric("batch_size", 100),
+ flag_string("activation1" .... [TRUNCATED]
> model = keras_model_sequential()
> model %>%
+ layer_dense(units=FLAGS$nodes1, activation=FLAGS$activation1, input_shape=dim(efw_train2)[2]) %>%
+ layer_dropout(FLAGS$dropout1) %> .... [TRUNCATED]
> model %>% compile(
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ loss = 'mse',
+ metrics = c('mse')
+ )
> model %>% fit(
+ as.matrix(efw_train2), train2Label,
+ epochs=FLAGS$epochs,
+ batch_size=FLAGS$batch_size,
+ validation_data=list(as.matrix( .... [TRUNCATED]
Train on 3021 samples, validate on 334 samples
Epoch 1/50
100/3021 [..............................] - ETA: 6s - loss: 39.7692 - mse: 39.7692
2200/3021 [====================>.........] - ETA: 0s - loss: 40.6391 - mse: 40.6391
3021/3021 [==============================] - 1s 260us/sample - loss: 40.5162 - mse: 40.5162 - val_loss: 38.7793 - val_mse: 38.7793
Epoch 2/50
100/3021 [..............................] - ETA: 0s - loss: 40.1121 - mse: 40.1121
2000/3021 [==================>...........] - ETA: 0s - loss: 38.1708 - mse: 38.1708
3021/3021 [==============================] - 0s 165us/sample - loss: 37.7172 - mse: 37.7172 - val_loss: 35.8920 - val_mse: 35.8920
Epoch 3/50
100/3021 [..............................] - ETA: 0s - loss: 35.6438 - mse: 35.6438
2000/3021 [==================>...........] - ETA: 0s - loss: 35.4248 - mse: 35.4248
3021/3021 [==============================] - 1s 171us/sample - loss: 34.8800 - mse: 34.8800 - val_loss: 33.1833 - val_mse: 33.1833
Epoch 4/50
100/3021 [..............................] - ETA: 0s - loss: 34.2790 - mse: 34.2790
2000/3021 [==================>...........] - ETA: 0s - loss: 32.9836 - mse: 32.9836
3021/3021 [==============================] - 0s 162us/sample - loss: 32.3770 - mse: 32.3770 - val_loss: 30.6765 - val_mse: 30.6765
Epoch 5/50
100/3021 [..............................] - ETA: 0s - loss: 30.9577 - mse: 30.9577
2100/3021 [===================>..........] - ETA: 0s - loss: 30.3058 - mse: 30.3058
3021/3021 [==============================] - 1s 166us/sample - loss: 29.8647 - mse: 29.8647 - val_loss: 28.3514 - val_mse: 28.3514
Epoch 6/50
100/3021 [..............................] - ETA: 0s - loss: 27.6673 - mse: 27.6673
2000/3021 [==================>...........] - ETA: 0s - loss: 28.1729 - mse: 28.1729
3021/3021 [==============================] - 1s 171us/sample - loss: 27.6446 - mse: 27.6446 - val_loss: 26.1599 - val_mse: 26.1599
Epoch 7/50
100/3021 [..............................] - ETA: 0s - loss: 26.5860 - mse: 26.5860
2200/3021 [====================>.........] - ETA: 0s - loss: 25.7088 - mse: 25.7088
3021/3021 [==============================] - 0s 158us/sample - loss: 25.5137 - mse: 25.5137 - val_loss: 24.1087 - val_mse: 24.1087
Epoch 8/50
100/3021 [..............................] - ETA: 0s - loss: 23.1362 - mse: 23.1362
2200/3021 [====================>.........] - ETA: 0s - loss: 23.6166 - mse: 23.6166
3021/3021 [==============================] - 0s 158us/sample - loss: 23.5402 - mse: 23.5402 - val_loss: 22.2323 - val_mse: 22.2323
Epoch 9/50
100/3021 [..............................] - ETA: 0s - loss: 22.7523 - mse: 22.7523
2200/3021 [====================>.........] - ETA: 0s - loss: 21.9002 - mse: 21.9002
3021/3021 [==============================] - 0s 157us/sample - loss: 21.6763 - mse: 21.6763 - val_loss: 20.5190 - val_mse: 20.5190
Epoch 10/50
100/3021 [..............................] - ETA: 0s - loss: 22.0503 - mse: 22.0503
1200/3021 [==========>...................] - ETA: 0s - loss: 20.6764 - mse: 20.6764
3021/3021 [==============================] - 1s 172us/sample - loss: 20.3611 - mse: 20.3611 - val_loss: 18.9627 - val_mse: 18.9627
Epoch 11/50
100/3021 [..............................] - ETA: 0s - loss: 18.6047 - mse: 18.6047
2100/3021 [===================>..........] - ETA: 0s - loss: 19.0466 - mse: 19.0466
3021/3021 [==============================] - 1s 170us/sample - loss: 18.7739 - mse: 18.7739 - val_loss: 17.5747 - val_mse: 17.5747
Epoch 12/50
100/3021 [..............................] - ETA: 0s - loss: 17.4693 - mse: 17.4693
2000/3021 [==================>...........] - ETA: 0s - loss: 17.7036 - mse: 17.7036
3021/3021 [==============================] - 0s 163us/sample - loss: 17.5224 - mse: 17.5224 - val_loss: 16.3482 - val_mse: 16.3482
Epoch 13/50
100/3021 [..............................] - ETA: 0s - loss: 16.5169 - mse: 16.5169
2100/3021 [===================>..........] - ETA: 0s - loss: 16.5323 - mse: 16.5323
3021/3021 [==============================] - 0s 162us/sample - loss: 16.3952 - mse: 16.3952 - val_loss: 15.2659 - val_mse: 15.2659
Epoch 14/50
100/3021 [..............................] - ETA: 0s - loss: 15.6277 - mse: 15.6277
1100/3021 [=========>....................] - ETA: 0s - loss: 15.8391 - mse: 15.8391
2000/3021 [==================>...........] - ETA: 0s - loss: 15.5464 - mse: 15.5464
3021/3021 [==============================] - 1s 219us/sample - loss: 15.4433 - mse: 15.4433 - val_loss: 14.2758 - val_mse: 14.2758
Epoch 15/50
100/3021 [..............................] - ETA: 0s - loss: 15.4478 - mse: 15.4478
2000/3021 [==================>...........] - ETA: 0s - loss: 14.6767 - mse: 14.6767
3021/3021 [==============================] - 0s 163us/sample - loss: 14.5819 - mse: 14.5819 - val_loss: 13.3985 - val_mse: 13.3985
Epoch 16/50
100/3021 [..............................] - ETA: 0s - loss: 12.4460 - mse: 12.4460
2200/3021 [====================>.........] - ETA: 0s - loss: 13.7061 - mse: 13.7061
3021/3021 [==============================] - 1s 166us/sample - loss: 13.7198 - mse: 13.7198 - val_loss: 12.6359 - val_mse: 12.6359
Epoch 17/50
100/3021 [..............................] - ETA: 0s - loss: 13.4301 - mse: 13.4301
2000/3021 [==================>...........] - ETA: 0s - loss: 13.4110 - mse: 13.4110
3021/3021 [==============================] - 0s 164us/sample - loss: 13.2440 - mse: 13.2440 - val_loss: 11.9420 - val_mse: 11.9420
Epoch 18/50
100/3021 [..............................] - ETA: 0s - loss: 13.5269 - mse: 13.5269
2400/3021 [======================>.......] - ETA: 0s - loss: 12.4700 - mse: 12.4700
3021/3021 [==============================] - 0s 154us/sample - loss: 12.4345 - mse: 12.4345 - val_loss: 11.3139 - val_mse: 11.3139
Epoch 19/50
100/3021 [..............................] - ETA: 0s - loss: 11.5404 - mse: 11.5404
2200/3021 [====================>.........] - ETA: 0s - loss: 12.1657 - mse: 12.1657
3021/3021 [==============================] - 0s 161us/sample - loss: 12.0281 - mse: 12.0281 - val_loss: 10.7466 - val_mse: 10.7466
Epoch 20/50
100/3021 [..............................] - ETA: 0s - loss: 11.2865 - mse: 11.2865
2300/3021 [=====================>........] - ETA: 0s - loss: 11.4561 - mse: 11.4561
3021/3021 [==============================] - 1s 179us/sample - loss: 11.3855 - mse: 11.3855 - val_loss: 10.2101 - val_mse: 10.2101
Epoch 21/50
100/3021 [..............................] - ETA: 0s - loss: 11.4464 - mse: 11.4464
1900/3021 [=================>............] - ETA: 0s - loss: 10.8971 - mse: 10.8971
3021/3021 [==============================] - 1s 179us/sample - loss: 10.8451 - mse: 10.8451 - val_loss: 9.7283 - val_mse: 9.7283
Epoch 22/50
100/3021 [..............................] - ETA: 0s - loss: 9.9668 - mse: 9.9668
2100/3021 [===================>..........] - ETA: 0s - loss: 10.6837 - mse: 10.6837
3021/3021 [==============================] - 0s 158us/sample - loss: 10.5772 - mse: 10.5772 - val_loss: 9.2745 - val_mse: 9.2745
Epoch 23/50
100/3021 [..............................] - ETA: 0s - loss: 11.1681 - mse: 11.1681
2300/3021 [=====================>........] - ETA: 0s - loss: 10.2219 - mse: 10.2219
3021/3021 [==============================] - 1s 166us/sample - loss: 10.2261 - mse: 10.2261 - val_loss: 8.8481 - val_mse: 8.8481
Epoch 24/50
100/3021 [..............................] - ETA: 0s - loss: 9.0246 - mse: 9.0246
1900/3021 [=================>............] - ETA: 0s - loss: 9.7531 - mse: 9.7531
3021/3021 [==============================] - 0s 164us/sample - loss: 9.7603 - mse: 9.7603 - val_loss: 8.4445 - val_mse: 8.4445
Epoch 25/50
100/3021 [..............................] - ETA: 0s - loss: 9.4129 - mse: 9.4129
2300/3021 [=====================>........] - ETA: 0s - loss: 9.4099 - mse: 9.4099
3021/3021 [==============================] - 0s 159us/sample - loss: 9.3349 - mse: 9.3349 - val_loss: 8.0592 - val_mse: 8.0592
Epoch 26/50
100/3021 [..............................] - ETA: 0s - loss: 10.0116 - mse: 10.0116
2300/3021 [=====================>........] - ETA: 0s - loss: 8.9963 - mse: 8.9963
3021/3021 [==============================] - 1s 195us/sample - loss: 9.0132 - mse: 9.0132 - val_loss: 7.6957 - val_mse: 7.6957
Epoch 27/50
100/3021 [..............................] - ETA: 0s - loss: 7.5793 - mse: 7.5793
2300/3021 [=====================>........] - ETA: 0s - loss: 8.6756 - mse: 8.6756
3021/3021 [==============================] - 0s 162us/sample - loss: 8.5276 - mse: 8.5276 - val_loss: 7.3456 - val_mse: 7.3456
Epoch 28/50
100/3021 [..............................] - ETA: 0s - loss: 9.1008 - mse: 9.1008
1700/3021 [===============>..............] - ETA: 0s - loss: 8.2086 - mse: 8.2086
3021/3021 [==============================] - 1s 210us/sample - loss: 8.1197 - mse: 8.1197 - val_loss: 7.0196 - val_mse: 7.0196
Epoch 29/50
100/3021 [..............................] - ETA: 0s - loss: 8.7029 - mse: 8.7029
2100/3021 [===================>..........] - ETA: 0s - loss: 8.0460 - mse: 8.0460
3021/3021 [==============================] - 0s 159us/sample - loss: 8.0317 - mse: 8.0317 - val_loss: 6.6996 - val_mse: 6.6996
Epoch 30/50
100/3021 [..............................] - ETA: 0s - loss: 6.6654 - mse: 6.6654
2100/3021 [===================>..........] - ETA: 0s - loss: 7.7421 - mse: 7.7421
3021/3021 [==============================] - 0s 162us/sample - loss: 7.7093 - mse: 7.7093 - val_loss: 6.3952 - val_mse: 6.3952
Epoch 31/50
100/3021 [..............................] - ETA: 0s - loss: 5.8185 - mse: 5.8185
2200/3021 [====================>.........] - ETA: 0s - loss: 7.2581 - mse: 7.2581
3021/3021 [==============================] - 1s 174us/sample - loss: 7.1968 - mse: 7.1968 - val_loss: 6.1050 - val_mse: 6.1050
Epoch 32/50
100/3021 [..............................] - ETA: 0s - loss: 6.5178 - mse: 6.5178
1900/3021 [=================>............] - ETA: 0s - loss: 6.8942 - mse: 6.8942
3021/3021 [==============================] - 1s 173us/sample - loss: 7.0044 - mse: 7.0044 - val_loss: 5.8312 - val_mse: 5.8312
Epoch 33/50
100/3021 [..............................] - ETA: 0s - loss: 7.2244 - mse: 7.2244
1400/3021 [============>.................] - ETA: 0s - loss: 6.9274 - mse: 6.9274
3021/3021 [==============================] - 0s 162us/sample - loss: 6.7792 - mse: 6.7792 - val_loss: 5.5651 - val_mse: 5.5651
Epoch 34/50
100/3021 [..............................] - ETA: 0s - loss: 6.7403 - mse: 6.7403
1400/3021 [============>.................] - ETA: 0s - loss: 6.6165 - mse: 6.6165
3021/3021 [==============================] - 1s 185us/sample - loss: 6.5779 - mse: 6.5779 - val_loss: 5.3088 - val_mse: 5.3088
Epoch 35/50
100/3021 [..............................] - ETA: 0s - loss: 7.3959 - mse: 7.3959
2000/3021 [==================>...........] - ETA: 0s - loss: 6.5604 - mse: 6.5604
3021/3021 [==============================] - 1s 168us/sample - loss: 6.3366 - mse: 6.3366 - val_loss: 5.0589 - val_mse: 5.0589
Epoch 36/50
100/3021 [..............................] - ETA: 0s - loss: 7.3142 - mse: 7.3142
2100/3021 [===================>..........] - ETA: 0s - loss: 6.1552 - mse: 6.1552
3021/3021 [==============================] - 0s 163us/sample - loss: 6.0407 - mse: 6.0407 - val_loss: 4.8227 - val_mse: 4.8227
Epoch 37/50
100/3021 [..............................] - ETA: 0s - loss: 5.4425 - mse: 5.4425
1600/3021 [==============>...............] - ETA: 0s - loss: 5.8282 - mse: 5.8282
3021/3021 [==============================] - 0s 165us/sample - loss: 5.8090 - mse: 5.8090 - val_loss: 4.5971 - val_mse: 4.5971
Epoch 38/50
100/3021 [..............................] - ETA: 0s - loss: 5.7417 - mse: 5.7417
2200/3021 [====================>.........] - ETA: 0s - loss: 5.4683 - mse: 5.4683
3021/3021 [==============================] - 1s 191us/sample - loss: 5.4722 - mse: 5.4722 - val_loss: 4.3786 - val_mse: 4.3786
Epoch 39/50
100/3021 [..............................] - ETA: 0s - loss: 5.4737 - mse: 5.4737
2200/3021 [====================>.........] - ETA: 0s - loss: 5.4501 - mse: 5.4501
3021/3021 [==============================] - 1s 166us/sample - loss: 5.4042 - mse: 5.4042 - val_loss: 4.1738 - val_mse: 4.1738
Epoch 40/50
100/3021 [..............................] - ETA: 0s - loss: 6.1317 - mse: 6.1317
2100/3021 [===================>..........] - ETA: 0s - loss: 5.3853 - mse: 5.3853
3021/3021 [==============================] - 1s 183us/sample - loss: 5.2024 - mse: 5.2024 - val_loss: 3.9673 - val_mse: 3.9673
Epoch 41/50
100/3021 [..............................] - ETA: 0s - loss: 3.9261 - mse: 3.9261
2000/3021 [==================>...........] - ETA: 0s - loss: 5.0176 - mse: 5.0176
3021/3021 [==============================] - 1s 174us/sample - loss: 4.9116 - mse: 4.9116 - val_loss: 3.7752 - val_mse: 3.7752
Epoch 42/50
100/3021 [..............................] - ETA: 0s - loss: 5.7887 - mse: 5.7887
2100/3021 [===================>..........] - ETA: 0s - loss: 4.8546 - mse: 4.8546
3021/3021 [==============================] - 1s 167us/sample - loss: 4.7614 - mse: 4.7614 - val_loss: 3.5877 - val_mse: 3.5877
Epoch 43/50
100/3021 [..............................] - ETA: 0s - loss: 4.5453 - mse: 4.5453
2200/3021 [====================>.........] - ETA: 0s - loss: 4.8455 - mse: 4.8455
3021/3021 [==============================] - 0s 161us/sample - loss: 4.7056 - mse: 4.7056 - val_loss: 3.4111 - val_mse: 3.4111
Epoch 44/50
100/3021 [..............................] - ETA: 0s - loss: 4.3489 - mse: 4.3489
1900/3021 [=================>............] - ETA: 0s - loss: 4.5136 - mse: 4.5136
3021/3021 [==============================] - 1s 194us/sample - loss: 4.4166 - mse: 4.4166 - val_loss: 3.2403 - val_mse: 3.2403
Epoch 45/50
100/3021 [..............................] - ETA: 0s - loss: 3.8791 - mse: 3.8791
2200/3021 [====================>.........] - ETA: 0s - loss: 4.2075 - mse: 4.2075
3021/3021 [==============================] - 1s 187us/sample - loss: 4.2361 - mse: 4.2361 - val_loss: 3.0790 - val_mse: 3.0790
Epoch 46/50
100/3021 [..............................] - ETA: 0s - loss: 3.4732 - mse: 3.4732
1900/3021 [=================>............] - ETA: 0s - loss: 4.2838 - mse: 4.2838
3021/3021 [==============================] - 0s 163us/sample - loss: 4.1001 - mse: 4.1001 - val_loss: 2.9230 - val_mse: 2.9230
Epoch 47/50
100/3021 [..............................] - ETA: 0s - loss: 3.9541 - mse: 3.9541
1900/3021 [=================>............] - ETA: 0s - loss: 3.9236 - mse: 3.9236
3021/3021 [==============================] - 1s 169us/sample - loss: 3.9456 - mse: 3.9456 - val_loss: 2.7725 - val_mse: 2.7725
Epoch 48/50
100/3021 [..............................] - ETA: 0s - loss: 4.6076 - mse: 4.6076
2400/3021 [======================>.......] - ETA: 0s - loss: 3.8498 - mse: 3.8498
3021/3021 [==============================] - 0s 154us/sample - loss: 3.7753 - mse: 3.7753 - val_loss: 2.6308 - val_mse: 2.6308
Epoch 49/50
100/3021 [..............................] - ETA: 0s - loss: 4.0109 - mse: 4.0109
1700/3021 [===============>..............] - ETA: 0s - loss: 3.6605 - mse: 3.6605
3021/3021 [==============================] - 0s 164us/sample - loss: 3.6229 - mse: 3.6229 - val_loss: 2.4998 - val_mse: 2.4998
Epoch 50/50
100/3021 [..............................] - ETA: 0s - loss: 4.0673 - mse: 4.0673
2000/3021 [==================>...........] - ETA: 0s - loss: 3.7184 - mse: 3.7184
3021/3021 [==============================] - 1s 167us/sample - loss: 3.6844 - mse: 3.6844 - val_loss: 2.3761 - val_mse: 2.3761Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-05-04T00-54-55Z
Training run 7/46 (flags = list(64, 392, 0.001, 200, 30, "tanh", "tanh", 0.5, 0.05))
Using run directory runs/2020-05-04T00-55-25Z
> FLAGS <- flags(
+ flag_numeric("nodes1", 128),
+ flag_numeric("nodes2", 128),
+ flag_numeric("batch_size", 100),
+ flag_string("activation1" .... [TRUNCATED]
> model = keras_model_sequential()
> model %>%
+ layer_dense(units=FLAGS$nodes1, activation=FLAGS$activation1, input_shape=dim(efw_train2)[2]) %>%
+ layer_dropout(FLAGS$dropout1) %> .... [TRUNCATED]
> model %>% compile(
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ loss = 'mse',
+ metrics = c('mse')
+ )
> model %>% fit(
+ as.matrix(efw_train2), train2Label,
+ epochs=FLAGS$epochs,
+ batch_size=FLAGS$batch_size,
+ validation_data=list(as.matrix( .... [TRUNCATED]
Train on 3021 samples, validate on 334 samples
Epoch 1/30
200/3021 [>.............................] - ETA: 3s - loss: 44.4046 - mse: 44.4046
3021/3021 [==============================] - 1s 256us/sample - loss: 41.5411 - mse: 41.5411 - val_loss: 39.0799 - val_mse: 39.0799
Epoch 2/30
200/3021 [>.............................] - ETA: 0s - loss: 38.5048 - mse: 38.5048
3021/3021 [==============================] - 0s 151us/sample - loss: 36.8317 - mse: 36.8317 - val_loss: 34.6772 - val_mse: 34.6772
Epoch 3/30
200/3021 [>.............................] - ETA: 0s - loss: 34.3276 - mse: 34.3276
3021/3021 [==============================] - 0s 154us/sample - loss: 32.4255 - mse: 32.4255 - val_loss: 29.9412 - val_mse: 29.9412
Epoch 4/30
200/3021 [>.............................] - ETA: 0s - loss: 29.2316 - mse: 29.2316
3021/3021 [==============================] - 0s 146us/sample - loss: 27.1630 - mse: 27.1630 - val_loss: 24.7629 - val_mse: 24.7629
Epoch 5/30
200/3021 [>.............................] - ETA: 0s - loss: 23.7485 - mse: 23.7485
3021/3021 [==============================] - 0s 150us/sample - loss: 21.7298 - mse: 21.7298 - val_loss: 19.3245 - val_mse: 19.3245
Epoch 6/30
200/3021 [>.............................] - ETA: 0s - loss: 19.5463 - mse: 19.5463
3021/3021 [==============================] - 0s 148us/sample - loss: 16.4947 - mse: 16.4947 - val_loss: 14.0931 - val_mse: 14.0931
Epoch 7/30
200/3021 [>.............................] - ETA: 0s - loss: 13.1877 - mse: 13.1877
2800/3021 [==========================>...] - ETA: 0s - loss: 11.7163 - mse: 11.7163
3021/3021 [==============================] - 0s 153us/sample - loss: 11.5481 - mse: 11.5481 - val_loss: 9.4058 - val_mse: 9.4058
Epoch 8/30
200/3021 [>.............................] - ETA: 0s - loss: 9.7053 - mse: 9.7053
3021/3021 [==============================] - 0s 149us/sample - loss: 7.7988 - mse: 7.7988 - val_loss: 5.7401 - val_mse: 5.7401
Epoch 9/30
200/3021 [>.............................] - ETA: 0s - loss: 5.9885 - mse: 5.9885
2600/3021 [========================>.....] - ETA: 0s - loss: 4.9472 - mse: 4.9472
3021/3021 [==============================] - 0s 143us/sample - loss: 4.8203 - mse: 4.8203 - val_loss: 3.0991 - val_mse: 3.0991
Epoch 10/30
200/3021 [>.............................] - ETA: 0s - loss: 3.5278 - mse: 3.5278
3021/3021 [==============================] - 0s 146us/sample - loss: 2.8658 - mse: 2.8658 - val_loss: 1.5576 - val_mse: 1.5576
Epoch 11/30
200/3021 [>.............................] - ETA: 0s - loss: 2.1882 - mse: 2.1882
3021/3021 [==============================] - 0s 137us/sample - loss: 1.9038 - mse: 1.9038 - val_loss: 0.7538 - val_mse: 0.7538
Epoch 12/30
200/3021 [>.............................] - ETA: 0s - loss: 1.6887 - mse: 1.6887
3021/3021 [==============================] - 0s 144us/sample - loss: 1.3135 - mse: 1.3135 - val_loss: 0.3957 - val_mse: 0.3957
Epoch 13/30
200/3021 [>.............................] - ETA: 0s - loss: 1.2045 - mse: 1.2045
3021/3021 [==============================] - 0s 151us/sample - loss: 1.1448 - mse: 1.1448 - val_loss: 0.2228 - val_mse: 0.2228
Epoch 14/30
200/3021 [>.............................] - ETA: 0s - loss: 1.4214 - mse: 1.4214
3021/3021 [==============================] - 0s 144us/sample - loss: 1.1666 - mse: 1.1666 - val_loss: 0.1637 - val_mse: 0.1637
Epoch 15/30
200/3021 [>.............................] - ETA: 0s - loss: 0.9019 - mse: 0.9019
3021/3021 [==============================] - 0s 139us/sample - loss: 1.0270 - mse: 1.0270 - val_loss: 0.1393 - val_mse: 0.1393
Epoch 16/30
200/3021 [>.............................] - ETA: 0s - loss: 1.1046 - mse: 1.1046
3021/3021 [==============================] - 0s 147us/sample - loss: 1.0707 - mse: 1.0707 - val_loss: 0.1177 - val_mse: 0.1177
Epoch 17/30
200/3021 [>.............................] - ETA: 0s - loss: 1.0689 - mse: 1.0689
3021/3021 [==============================] - 0s 140us/sample - loss: 1.0025 - mse: 1.0025 - val_loss: 0.1149 - val_mse: 0.1149
Epoch 18/30
200/3021 [>.............................] - ETA: 0s - loss: 1.0836 - mse: 1.0836
3021/3021 [==============================] - 0s 137us/sample - loss: 1.0022 - mse: 1.0022 - val_loss: 0.1017 - val_mse: 0.1017
Epoch 19/30
200/3021 [>.............................] - ETA: 0s - loss: 0.9949 - mse: 0.9949
3021/3021 [==============================] - 0s 144us/sample - loss: 0.9650 - mse: 0.9650 - val_loss: 0.0942 - val_mse: 0.0942
Epoch 20/30
200/3021 [>.............................] - ETA: 0s - loss: 0.9478 - mse: 0.9478
2600/3021 [========================>.....] - ETA: 0s - loss: 0.9642 - mse: 0.9642
3021/3021 [==============================] - 0s 149us/sample - loss: 0.9782 - mse: 0.9782 - val_loss: 0.0948 - val_mse: 0.0948
Epoch 21/30
200/3021 [>.............................] - ETA: 0s - loss: 0.9732 - mse: 0.9732
3021/3021 [==============================] - 0s 147us/sample - loss: 0.9874 - mse: 0.9874 - val_loss: 0.0887 - val_mse: 0.0887
Epoch 22/30
200/3021 [>.............................] - ETA: 0s - loss: 0.7413 - mse: 0.7413
2600/3021 [========================>.....] - ETA: 0s - loss: 0.9607 - mse: 0.9607
3021/3021 [==============================] - 0s 148us/sample - loss: 0.9509 - mse: 0.9509 - val_loss: 0.0787 - val_mse: 0.0787
Epoch 23/30
200/3021 [>.............................] - ETA: 0s - loss: 0.9619 - mse: 0.9619
3021/3021 [==============================] - 0s 143us/sample - loss: 0.9696 - mse: 0.9696 - val_loss: 0.0806 - val_mse: 0.0806
Epoch 24/30
200/3021 [>.............................] - ETA: 0s - loss: 0.8600 - mse: 0.8600
3021/3021 [==============================] - 0s 137us/sample - loss: 0.9144 - mse: 0.9144 - val_loss: 0.0853 - val_mse: 0.0853
Epoch 25/30
200/3021 [>.............................] - ETA: 0s - loss: 0.7664 - mse: 0.7664
3000/3021 [============================>.] - ETA: 0s - loss: 0.9428 - mse: 0.9428
3021/3021 [==============================] - 0s 146us/sample - loss: 0.9432 - mse: 0.9432 - val_loss: 0.0795 - val_mse: 0.0795
Epoch 26/30
200/3021 [>.............................] - ETA: 0s - loss: 1.0252 - mse: 1.0252
3021/3021 [==============================] - 0s 144us/sample - loss: 0.8984 - mse: 0.8984 - val_loss: 0.0774 - val_mse: 0.0774
Epoch 27/30
200/3021 [>.............................] - ETA: 0s - loss: 0.9311 - mse: 0.9311
3021/3021 [==============================] - 0s 136us/sample - loss: 0.9004 - mse: 0.9004 - val_loss: 0.0734 - val_mse: 0.0734
Epoch 28/30
200/3021 [>.............................] - ETA: 0s - loss: 0.9669 - mse: 0.9669
2400/3021 [======================>.......] - ETA: 0s - loss: 0.8883 - mse: 0.8883
3021/3021 [==============================] - 0s 156us/sample - loss: 0.8928 - mse: 0.8928 - val_loss: 0.0676 - val_mse: 0.0676
Epoch 29/30
200/3021 [>.............................] - ETA: 0s - loss: 0.7796 - mse: 0.7796
3021/3021 [==============================] - 0s 142us/sample - loss: 0.8620 - mse: 0.8620 - val_loss: 0.0669 - val_mse: 0.0669
Epoch 30/30
200/3021 [>.............................] - ETA: 0s - loss: 0.8808 - mse: 0.8808
3000/3021 [============================>.] - ETA: 0s - loss: 0.9010 - mse: 0.9010
3021/3021 [==============================] - 0s 145us/sample - loss: 0.9037 - mse: 0.9037 - val_loss: 0.0615 - val_mse: 0.0615Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-05-04T00-55-25Z
Training run 8/46 (flags = list(128, 128, 0.01, 200, 50, "tanh", "relu", 0.2, 0.2))
Using run directory runs/2020-05-04T00-55-42Z
> FLAGS <- flags(
+ flag_numeric("nodes1", 128),
+ flag_numeric("nodes2", 128),
+ flag_numeric("batch_size", 100),
+ flag_string("activation1" .... [TRUNCATED]
> model = keras_model_sequential()
> model %>%
+ layer_dense(units=FLAGS$nodes1, activation=FLAGS$activation1, input_shape=dim(efw_train2)[2]) %>%
+ layer_dropout(FLAGS$dropout1) %> .... [TRUNCATED]
> model %>% compile(
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ loss = 'mse',
+ metrics = c('mse')
+ )
> model %>% fit(
+ as.matrix(efw_train2), train2Label,
+ epochs=FLAGS$epochs,
+ batch_size=FLAGS$batch_size,
+ validation_data=list(as.matrix( .... [TRUNCATED]
Train on 3021 samples, validate on 334 samples
Epoch 1/50
200/3021 [>.............................] - ETA: 3s - loss: 43.6796 - mse: 43.6796
3021/3021 [==============================] - 1s 243us/sample - loss: 17.2517 - mse: 17.2517 - val_loss: 3.7465 - val_mse: 3.7465
Epoch 2/50
200/3021 [>.............................] - ETA: 0s - loss: 3.9663 - mse: 3.9663
3021/3021 [==============================] - 0s 148us/sample - loss: 2.5667 - mse: 2.5667 - val_loss: 1.7636 - val_mse: 1.7636
Epoch 3/50
200/3021 [>.............................] - ETA: 0s - loss: 1.8893 - mse: 1.8893
3021/3021 [==============================] - 0s 152us/sample - loss: 0.8906 - mse: 0.8906 - val_loss: 0.3646 - val_mse: 0.3646
Epoch 4/50
200/3021 [>.............................] - ETA: 0s - loss: 0.5783 - mse: 0.5783
2600/3021 [========================>.....] - ETA: 0s - loss: 0.4321 - mse: 0.4321
3021/3021 [==============================] - 0s 144us/sample - loss: 0.4396 - mse: 0.4396 - val_loss: 0.1385 - val_mse: 0.1385
Epoch 5/50
200/3021 [>.............................] - ETA: 0s - loss: 0.3322 - mse: 0.3322
3021/3021 [==============================] - 0s 146us/sample - loss: 0.3329 - mse: 0.3329 - val_loss: 0.1163 - val_mse: 0.1163
Epoch 6/50
200/3021 [>.............................] - ETA: 0s - loss: 0.3208 - mse: 0.3208
3021/3021 [==============================] - 0s 147us/sample - loss: 0.2933 - mse: 0.2933 - val_loss: 0.0761 - val_mse: 0.0761
Epoch 7/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2484 - mse: 0.2484
2400/3021 [======================>.......] - ETA: 0s - loss: 0.2838 - mse: 0.2838
3021/3021 [==============================] - 0s 146us/sample - loss: 0.2854 - mse: 0.2854 - val_loss: 0.0750 - val_mse: 0.0750
Epoch 8/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2205 - mse: 0.2205
3021/3021 [==============================] - 0s 149us/sample - loss: 0.2442 - mse: 0.2442 - val_loss: 0.0710 - val_mse: 0.0710
Epoch 9/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2392 - mse: 0.2392
2800/3021 [==========================>...] - ETA: 0s - loss: 0.2366 - mse: 0.2366
3021/3021 [==============================] - 0s 156us/sample - loss: 0.2350 - mse: 0.2350 - val_loss: 0.0728 - val_mse: 0.0728
Epoch 10/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1876 - mse: 0.1876
3021/3021 [==============================] - 0s 152us/sample - loss: 0.2326 - mse: 0.2326 - val_loss: 0.0775 - val_mse: 0.0775
Epoch 11/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2296 - mse: 0.2296
2600/3021 [========================>.....] - ETA: 0s - loss: 0.2126 - mse: 0.2126
3021/3021 [==============================] - 0s 145us/sample - loss: 0.2122 - mse: 0.2122 - val_loss: 0.1046 - val_mse: 0.1046
Epoch 12/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2319 - mse: 0.2319
3021/3021 [==============================] - 0s 148us/sample - loss: 0.1949 - mse: 0.1949 - val_loss: 0.1376 - val_mse: 0.1376
Epoch 13/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2456 - mse: 0.2456
3021/3021 [==============================] - 0s 147us/sample - loss: 0.2411 - mse: 0.2411 - val_loss: 0.1198 - val_mse: 0.1198
Epoch 14/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2212 - mse: 0.2212
3021/3021 [==============================] - 0s 148us/sample - loss: 0.2267 - mse: 0.2267 - val_loss: 0.0972 - val_mse: 0.0972
Epoch 15/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2108 - mse: 0.2108
2600/3021 [========================>.....] - ETA: 0s - loss: 0.1955 - mse: 0.1955
3021/3021 [==============================] - 0s 149us/sample - loss: 0.1945 - mse: 0.1945 - val_loss: 0.0774 - val_mse: 0.0774
Epoch 16/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2306 - mse: 0.2306
3021/3021 [==============================] - 0s 156us/sample - loss: 0.1804 - mse: 0.1804 - val_loss: 0.0768 - val_mse: 0.0768
Epoch 17/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2019 - mse: 0.2019
3021/3021 [==============================] - 0s 147us/sample - loss: 0.1990 - mse: 0.1990 - val_loss: 0.1277 - val_mse: 0.1277
Epoch 18/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1806 - mse: 0.1806
3021/3021 [==============================] - 0s 140us/sample - loss: 0.2025 - mse: 0.2025 - val_loss: 0.0883 - val_mse: 0.0883
Epoch 19/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1611 - mse: 0.1611
3021/3021 [==============================] - 0s 152us/sample - loss: 0.1796 - mse: 0.1796 - val_loss: 0.0583 - val_mse: 0.0583
Epoch 20/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1686 - mse: 0.1686
2800/3021 [==========================>...] - ETA: 0s - loss: 0.1849 - mse: 0.1849
3021/3021 [==============================] - 0s 153us/sample - loss: 0.1877 - mse: 0.1877 - val_loss: 0.1200 - val_mse: 0.1200
Epoch 21/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2400 - mse: 0.2400
3021/3021 [==============================] - 0s 142us/sample - loss: 0.1738 - mse: 0.1738 - val_loss: 0.0849 - val_mse: 0.0849
Epoch 22/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1609 - mse: 0.1609
2000/3021 [==================>...........] - ETA: 0s - loss: 0.1736 - mse: 0.1736
3021/3021 [==============================] - 0s 151us/sample - loss: 0.1689 - mse: 0.1689 - val_loss: 0.0736 - val_mse: 0.0736
Epoch 23/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1934 - mse: 0.1934
3021/3021 [==============================] - 0s 143us/sample - loss: 0.1770 - mse: 0.1770 - val_loss: 0.1207 - val_mse: 0.1207
Epoch 24/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1753 - mse: 0.1753
3021/3021 [==============================] - 0s 137us/sample - loss: 0.1749 - mse: 0.1749 - val_loss: 0.0574 - val_mse: 0.0574
Epoch 25/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1311 - mse: 0.1311
3021/3021 [==============================] - 0s 146us/sample - loss: 0.1627 - mse: 0.1627 - val_loss: 0.0576 - val_mse: 0.0576
Epoch 26/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1797 - mse: 0.1797
2800/3021 [==========================>...] - ETA: 0s - loss: 0.1633 - mse: 0.1633
3021/3021 [==============================] - 0s 147us/sample - loss: 0.1617 - mse: 0.1617 - val_loss: 0.0625 - val_mse: 0.0625
Epoch 27/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1586 - mse: 0.1586
2600/3021 [========================>.....] - ETA: 0s - loss: 0.1726 - mse: 0.1726
3021/3021 [==============================] - 0s 148us/sample - loss: 0.1724 - mse: 0.1724 - val_loss: 0.1111 - val_mse: 0.1111
Epoch 28/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1617 - mse: 0.1617
2400/3021 [======================>.......] - ETA: 0s - loss: 0.2138 - mse: 0.2138
3021/3021 [==============================] - 0s 155us/sample - loss: 0.2084 - mse: 0.2084 - val_loss: 0.0761 - val_mse: 0.0761
Epoch 29/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1615 - mse: 0.1615
3021/3021 [==============================] - 0s 138us/sample - loss: 0.1601 - mse: 0.1601 - val_loss: 0.0844 - val_mse: 0.0844
Epoch 30/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1577 - mse: 0.1577
3021/3021 [==============================] - 0s 152us/sample - loss: 0.1652 - mse: 0.1652 - val_loss: 0.0556 - val_mse: 0.0556
Epoch 31/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1500 - mse: 0.1500
3021/3021 [==============================] - 0s 144us/sample - loss: 0.1400 - mse: 0.1400 - val_loss: 0.0951 - val_mse: 0.0951
Epoch 32/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1451 - mse: 0.1451
3021/3021 [==============================] - 0s 143us/sample - loss: 0.1503 - mse: 0.1503 - val_loss: 0.0782 - val_mse: 0.0782
Epoch 33/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1537 - mse: 0.1537
2800/3021 [==========================>...] - ETA: 0s - loss: 0.1601 - mse: 0.1601
3021/3021 [==============================] - 0s 152us/sample - loss: 0.1591 - mse: 0.1591 - val_loss: 0.0657 - val_mse: 0.0657
Epoch 34/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1436 - mse: 0.1436
3021/3021 [==============================] - 0s 140us/sample - loss: 0.1384 - mse: 0.1384 - val_loss: 0.0618 - val_mse: 0.0618
Epoch 35/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1259 - mse: 0.1259
3021/3021 [==============================] - 0s 145us/sample - loss: 0.1375 - mse: 0.1375 - val_loss: 0.0836 - val_mse: 0.0836
Epoch 36/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1431 - mse: 0.1431
3021/3021 [==============================] - 0s 141us/sample - loss: 0.1420 - mse: 0.1420 - val_loss: 0.0717 - val_mse: 0.0717
Epoch 37/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1182 - mse: 0.1182
2600/3021 [========================>.....] - ETA: 0s - loss: 0.1352 - mse: 0.1352
3021/3021 [==============================] - 0s 150us/sample - loss: 0.1338 - mse: 0.1338 - val_loss: 0.0602 - val_mse: 0.0602
Epoch 38/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1097 - mse: 0.1097
3021/3021 [==============================] - 0s 146us/sample - loss: 0.1341 - mse: 0.1341 - val_loss: 0.0523 - val_mse: 0.0523
Epoch 39/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1228 - mse: 0.1228
3021/3021 [==============================] - 0s 140us/sample - loss: 0.1423 - mse: 0.1423 - val_loss: 0.0735 - val_mse: 0.0735
Epoch 40/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1108 - mse: 0.1108
3021/3021 [==============================] - 0s 145us/sample - loss: 0.1478 - mse: 0.1478 - val_loss: 0.0845 - val_mse: 0.0845
Epoch 41/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1767 - mse: 0.1767
3021/3021 [==============================] - 0s 145us/sample - loss: 0.1344 - mse: 0.1344 - val_loss: 0.0603 - val_mse: 0.0603
Epoch 42/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1081 - mse: 0.1081
2600/3021 [========================>.....] - ETA: 0s - loss: 0.1340 - mse: 0.1340
3021/3021 [==============================] - 0s 153us/sample - loss: 0.1332 - mse: 0.1332 - val_loss: 0.0515 - val_mse: 0.0515
Epoch 43/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1146 - mse: 0.1146
2800/3021 [==========================>...] - ETA: 0s - loss: 0.1285 - mse: 0.1285
3021/3021 [==============================] - 0s 147us/sample - loss: 0.1296 - mse: 0.1296 - val_loss: 0.0595 - val_mse: 0.0595
Epoch 44/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1179 - mse: 0.1179
3021/3021 [==============================] - 0s 136us/sample - loss: 0.1251 - mse: 0.1251 - val_loss: 0.0515 - val_mse: 0.0515
Epoch 45/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1446 - mse: 0.1446
3021/3021 [==============================] - 0s 137us/sample - loss: 0.1225 - mse: 0.1225 - val_loss: 0.0666 - val_mse: 0.0666
Epoch 46/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1220 - mse: 0.1220
3021/3021 [==============================] - 0s 149us/sample - loss: 0.1225 - mse: 0.1225 - val_loss: 0.0823 - val_mse: 0.0823
Epoch 47/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1559 - mse: 0.1559
3021/3021 [==============================] - 0s 141us/sample - loss: 0.1276 - mse: 0.1276 - val_loss: 0.0502 - val_mse: 0.0502
Epoch 48/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1358 - mse: 0.1358
3021/3021 [==============================] - 0s 145us/sample - loss: 0.1200 - mse: 0.1200 - val_loss: 0.0673 - val_mse: 0.0673
Epoch 49/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1189 - mse: 0.1189
2800/3021 [==========================>...] - ETA: 0s - loss: 0.1225 - mse: 0.1225
3021/3021 [==============================] - 0s 143us/sample - loss: 0.1220 - mse: 0.1220 - val_loss: 0.0573 - val_mse: 0.0573
Epoch 50/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1528 - mse: 0.1528
3021/3021 [==============================] - 0s 149us/sample - loss: 0.1213 - mse: 0.1213 - val_loss: 0.0504 - val_mse: 0.0504Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-05-04T00-55-42Z
Training run 9/46 (flags = list(128, 64, 0.001, 100, 100, "relu", "tanh", 0.5, 0.1))
Using run directory runs/2020-05-04T00-56-08Z
> FLAGS <- flags(
+ flag_numeric("nodes1", 128),
+ flag_numeric("nodes2", 128),
+ flag_numeric("batch_size", 100),
+ flag_string("activation1" .... [TRUNCATED]
> model = keras_model_sequential()
> model %>%
+ layer_dense(units=FLAGS$nodes1, activation=FLAGS$activation1, input_shape=dim(efw_train2)[2]) %>%
+ layer_dropout(FLAGS$dropout1) %> .... [TRUNCATED]
> model %>% compile(
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ loss = 'mse',
+ metrics = c('mse')
+ )
> model %>% fit(
+ as.matrix(efw_train2), train2Label,
+ epochs=FLAGS$epochs,
+ batch_size=FLAGS$batch_size,
+ validation_data=list(as.matrix( .... [TRUNCATED]
Train on 3021 samples, validate on 334 samples
Epoch 1/100
100/3021 [..............................] - ETA: 7s - loss: 43.1583 - mse: 43.1583
2500/3021 [=======================>......] - ETA: 0s - loss: 31.7013 - mse: 31.7013
3021/3021 [==============================] - 1s 252us/sample - loss: 29.8662 - mse: 29.8662 - val_loss: 18.7323 - val_mse: 18.7323
Epoch 2/100
100/3021 [..............................] - ETA: 0s - loss: 18.9744 - mse: 18.9744
2000/3021 [==================>...........] - ETA: 0s - loss: 15.2825 - mse: 15.2825
3021/3021 [==============================] - 0s 165us/sample - loss: 13.9791 - mse: 13.9791 - val_loss: 8.9441 - val_mse: 8.9441
Epoch 3/100
100/3021 [..............................] - ETA: 0s - loss: 9.3554 - mse: 9.3554
2000/3021 [==================>...........] - ETA: 0s - loss: 8.8031 - mse: 8.8031
3021/3021 [==============================] - 1s 166us/sample - loss: 8.2061 - mse: 8.2061 - val_loss: 5.2643 - val_mse: 5.2643
Epoch 4/100
100/3021 [..............................] - ETA: 0s - loss: 5.9867 - mse: 5.9867
2300/3021 [=====================>........] - ETA: 0s - loss: 5.6692 - mse: 5.6692
3021/3021 [==============================] - 0s 153us/sample - loss: 5.3777 - mse: 5.3777 - val_loss: 3.2316 - val_mse: 3.2316
Epoch 5/100
100/3021 [..............................] - ETA: 0s - loss: 4.4209 - mse: 4.4209
2000/3021 [==================>...........] - ETA: 0s - loss: 3.9144 - mse: 3.9144
3021/3021 [==============================] - 1s 188us/sample - loss: 3.7200 - mse: 3.7200 - val_loss: 1.9692 - val_mse: 1.9692
Epoch 6/100
100/3021 [..............................] - ETA: 0s - loss: 2.6062 - mse: 2.6062
2000/3021 [==================>...........] - ETA: 0s - loss: 2.7893 - mse: 2.7893
3021/3021 [==============================] - 1s 170us/sample - loss: 2.7239 - mse: 2.7239 - val_loss: 1.2611 - val_mse: 1.2611
Epoch 7/100
100/3021 [..............................] - ETA: 0s - loss: 2.5698 - mse: 2.5698
1600/3021 [==============>...............] - ETA: 0s - loss: 2.1914 - mse: 2.1914
3021/3021 [==============================] - 1s 181us/sample - loss: 2.1149 - mse: 2.1149 - val_loss: 0.8746 - val_mse: 0.8746
Epoch 8/100
100/3021 [..............................] - ETA: 0s - loss: 2.0859 - mse: 2.0859
1900/3021 [=================>............] - ETA: 0s - loss: 1.8364 - mse: 1.8364
3021/3021 [==============================] - 0s 157us/sample - loss: 1.7436 - mse: 1.7436 - val_loss: 0.6731 - val_mse: 0.6731
Epoch 9/100
100/3021 [..............................] - ETA: 0s - loss: 1.6458 - mse: 1.6458
1700/3021 [===============>..............] - ETA: 0s - loss: 1.5465 - mse: 1.5465
3021/3021 [==============================] - 0s 164us/sample - loss: 1.5497 - mse: 1.5497 - val_loss: 0.5559 - val_mse: 0.5559
Epoch 10/100
100/3021 [..............................] - ETA: 0s - loss: 1.4076 - mse: 1.4076
2300/3021 [=====================>........] - ETA: 0s - loss: 1.4119 - mse: 1.4119
3021/3021 [==============================] - 0s 153us/sample - loss: 1.3999 - mse: 1.3999 - val_loss: 0.4629 - val_mse: 0.4629
Epoch 11/100
100/3021 [..............................] - ETA: 0s - loss: 1.3367 - mse: 1.3367
1100/3021 [=========>....................] - ETA: 0s - loss: 1.3202 - mse: 1.3202
3021/3021 [==============================] - 1s 177us/sample - loss: 1.3163 - mse: 1.3163 - val_loss: 0.4088 - val_mse: 0.4088
Epoch 12/100
100/3021 [..............................] - ETA: 0s - loss: 1.3547 - mse: 1.3547
2300/3021 [=====================>........] - ETA: 0s - loss: 1.3175 - mse: 1.3175
3021/3021 [==============================] - 0s 153us/sample - loss: 1.2978 - mse: 1.2978 - val_loss: 0.3745 - val_mse: 0.3745
Epoch 13/100
100/3021 [..............................] - ETA: 0s - loss: 1.7373 - mse: 1.7373
2000/3021 [==================>...........] - ETA: 0s - loss: 1.2689 - mse: 1.2689
3021/3021 [==============================] - 0s 164us/sample - loss: 1.2576 - mse: 1.2576 - val_loss: 0.3312 - val_mse: 0.3312
Epoch 14/100
100/3021 [..............................] - ETA: 0s - loss: 1.0892 - mse: 1.0892
1100/3021 [=========>....................] - ETA: 0s - loss: 1.1719 - mse: 1.1719
3021/3021 [==============================] - 0s 158us/sample - loss: 1.2036 - mse: 1.2036 - val_loss: 0.3134 - val_mse: 0.3134
Epoch 15/100
100/3021 [..............................] - ETA: 0s - loss: 1.0390 - mse: 1.0390
2000/3021 [==================>...........] - ETA: 0s - loss: 1.1585 - mse: 1.1585
3021/3021 [==============================] - 0s 156us/sample - loss: 1.1477 - mse: 1.1477 - val_loss: 0.3082 - val_mse: 0.3082
Epoch 16/100
100/3021 [..............................] - ETA: 0s - loss: 1.0508 - mse: 1.0508
2300/3021 [=====================>........] - ETA: 0s - loss: 1.1054 - mse: 1.1054
3021/3021 [==============================] - 0s 154us/sample - loss: 1.0884 - mse: 1.0884 - val_loss: 0.2715 - val_mse: 0.2715
Epoch 17/100
100/3021 [..............................] - ETA: 0s - loss: 1.1559 - mse: 1.1559
2300/3021 [=====================>........] - ETA: 0s - loss: 1.0629 - mse: 1.0629
3021/3021 [==============================] - 0s 159us/sample - loss: 1.0751 - mse: 1.0751 - val_loss: 0.2659 - val_mse: 0.2659
Epoch 18/100
100/3021 [..............................] - ETA: 0s - loss: 0.9495 - mse: 0.9495
2400/3021 [======================>.......] - ETA: 0s - loss: 1.0635 - mse: 1.0635
3021/3021 [==============================] - 0s 163us/sample - loss: 1.0557 - mse: 1.0557 - val_loss: 0.2373 - val_mse: 0.2373
Epoch 19/100
100/3021 [..............................] - ETA: 0s - loss: 0.7913 - mse: 0.7913
2100/3021 [===================>..........] - ETA: 0s - loss: 0.9977 - mse: 0.9977
3021/3021 [==============================] - 0s 150us/sample - loss: 1.0026 - mse: 1.0026 - val_loss: 0.2252 - val_mse: 0.2252
Epoch 20/100
100/3021 [..............................] - ETA: 0s - loss: 0.8154 - mse: 0.8154
2000/3021 [==================>...........] - ETA: 0s - loss: 1.0114 - mse: 1.0114
3021/3021 [==============================] - 0s 154us/sample - loss: 1.0056 - mse: 1.0056 - val_loss: 0.1981 - val_mse: 0.1981
Epoch 21/100
100/3021 [..............................] - ETA: 0s - loss: 0.8613 - mse: 0.8613
2000/3021 [==================>...........] - ETA: 0s - loss: 0.9663 - mse: 0.9663
3021/3021 [==============================] - 0s 157us/sample - loss: 0.9658 - mse: 0.9658 - val_loss: 0.2082 - val_mse: 0.2082
Epoch 22/100
100/3021 [..............................] - ETA: 0s - loss: 1.0258 - mse: 1.0258
1900/3021 [=================>............] - ETA: 0s - loss: 0.9251 - mse: 0.9251
3021/3021 [==============================] - 0s 157us/sample - loss: 0.9569 - mse: 0.9569 - val_loss: 0.2098 - val_mse: 0.2098
Epoch 23/100
100/3021 [..............................] - ETA: 0s - loss: 1.0020 - mse: 1.0020
2100/3021 [===================>..........] - ETA: 0s - loss: 0.9310 - mse: 0.9310
3021/3021 [==============================] - 0s 161us/sample - loss: 0.9162 - mse: 0.9162 - val_loss: 0.1812 - val_mse: 0.1812
Epoch 24/100
100/3021 [..............................] - ETA: 0s - loss: 1.0027 - mse: 1.0027
1400/3021 [============>.................] - ETA: 0s - loss: 0.9737 - mse: 0.9737
3021/3021 [==============================] - 0s 161us/sample - loss: 0.9718 - mse: 0.9718 - val_loss: 0.1800 - val_mse: 0.1800
Epoch 25/100
100/3021 [..............................] - ETA: 0s - loss: 0.7692 - mse: 0.7692
1700/3021 [===============>..............] - ETA: 0s - loss: 0.9041 - mse: 0.9041
3021/3021 [==============================] - 0s 158us/sample - loss: 0.9324 - mse: 0.9324 - val_loss: 0.1598 - val_mse: 0.1598
Epoch 26/100
100/3021 [..............................] - ETA: 0s - loss: 0.9951 - mse: 0.9951
2200/3021 [====================>.........] - ETA: 0s - loss: 0.8636 - mse: 0.8636
3021/3021 [==============================] - 0s 147us/sample - loss: 0.8604 - mse: 0.8604 - val_loss: 0.1681 - val_mse: 0.1681
Epoch 27/100
100/3021 [..............................] - ETA: 0s - loss: 1.1712 - mse: 1.1712
2300/3021 [=====================>........] - ETA: 0s - loss: 0.9147 - mse: 0.9147
3021/3021 [==============================] - 0s 151us/sample - loss: 0.9137 - mse: 0.9137 - val_loss: 0.1422 - val_mse: 0.1422
Epoch 28/100
100/3021 [..............................] - ETA: 0s - loss: 0.8361 - mse: 0.8361
2200/3021 [====================>.........] - ETA: 0s - loss: 0.8674 - mse: 0.8674
3021/3021 [==============================] - 0s 159us/sample - loss: 0.8613 - mse: 0.8613 - val_loss: 0.1670 - val_mse: 0.1670
Epoch 29/100
100/3021 [..............................] - ETA: 0s - loss: 1.0108 - mse: 1.0108
1400/3021 [============>.................] - ETA: 0s - loss: 0.8818 - mse: 0.8818
3021/3021 [==============================] - 0s 158us/sample - loss: 0.8562 - mse: 0.8562 - val_loss: 0.1448 - val_mse: 0.1448
Epoch 30/100
100/3021 [..............................] - ETA: 0s - loss: 0.7408 - mse: 0.7408
1700/3021 [===============>..............] - ETA: 0s - loss: 0.8412 - mse: 0.8412
3021/3021 [==============================] - 0s 164us/sample - loss: 0.8312 - mse: 0.8312 - val_loss: 0.1380 - val_mse: 0.1380
Epoch 31/100
100/3021 [..............................] - ETA: 0s - loss: 0.7734 - mse: 0.7734
1000/3021 [========>.....................] - ETA: 0s - loss: 0.7330 - mse: 0.7330
3021/3021 [==============================] - 0s 164us/sample - loss: 0.7866 - mse: 0.7866 - val_loss: 0.1482 - val_mse: 0.1482
Epoch 32/100
100/3021 [..............................] - ETA: 0s - loss: 0.8201 - mse: 0.8201
2300/3021 [=====================>........] - ETA: 0s - loss: 0.8455 - mse: 0.8455
3021/3021 [==============================] - 0s 155us/sample - loss: 0.8377 - mse: 0.8377 - val_loss: 0.1326 - val_mse: 0.1326
Epoch 33/100
100/3021 [..............................] - ETA: 0s - loss: 0.8153 - mse: 0.8153
1200/3021 [==========>...................] - ETA: 0s - loss: 0.7904 - mse: 0.7904
3021/3021 [==============================] - 0s 154us/sample - loss: 0.8010 - mse: 0.8010 - val_loss: 0.1175 - val_mse: 0.1175
Epoch 34/100
100/3021 [..............................] - ETA: 0s - loss: 0.7130 - mse: 0.7130
2400/3021 [======================>.......] - ETA: 0s - loss: 0.7553 - mse: 0.7553
3021/3021 [==============================] - 0s 152us/sample - loss: 0.7592 - mse: 0.7592 - val_loss: 0.1258 - val_mse: 0.1258
Epoch 35/100
100/3021 [..............................] - ETA: 0s - loss: 0.6526 - mse: 0.6526
2300/3021 [=====================>........] - ETA: 0s - loss: 0.7413 - mse: 0.7413
3021/3021 [==============================] - 0s 153us/sample - loss: 0.7274 - mse: 0.7274 - val_loss: 0.1042 - val_mse: 0.1042
Epoch 36/100
100/3021 [..............................] - ETA: 0s - loss: 0.6327 - mse: 0.6327
2100/3021 [===================>..........] - ETA: 0s - loss: 0.7503 - mse: 0.7503
3021/3021 [==============================] - 0s 157us/sample - loss: 0.7422 - mse: 0.7422 - val_loss: 0.1095 - val_mse: 0.1095
Epoch 37/100
100/3021 [..............................] - ETA: 0s - loss: 0.6943 - mse: 0.6943
2100/3021 [===================>..........] - ETA: 0s - loss: 0.7296 - mse: 0.7296
3021/3021 [==============================] - 0s 160us/sample - loss: 0.7520 - mse: 0.7520 - val_loss: 0.1354 - val_mse: 0.1354
Epoch 38/100
100/3021 [..............................] - ETA: 0s - loss: 0.7682 - mse: 0.7682
1800/3021 [================>.............] - ETA: 0s - loss: 0.7325 - mse: 0.7325
3021/3021 [==============================] - 0s 163us/sample - loss: 0.7435 - mse: 0.7435 - val_loss: 0.1072 - val_mse: 0.1072
Epoch 39/100
100/3021 [..............................] - ETA: 0s - loss: 0.6299 - mse: 0.6299
1800/3021 [================>.............] - ETA: 0s - loss: 0.7762 - mse: 0.7762
3021/3021 [==============================] - 0s 161us/sample - loss: 0.7574 - mse: 0.7574 - val_loss: 0.1069 - val_mse: 0.1069
Epoch 40/100
100/3021 [..............................] - ETA: 0s - loss: 0.6195 - mse: 0.6195
2000/3021 [==================>...........] - ETA: 0s - loss: 0.7479 - mse: 0.7479
3021/3021 [==============================] - 0s 160us/sample - loss: 0.7336 - mse: 0.7336 - val_loss: 0.1083 - val_mse: 0.1083
Epoch 41/100
100/3021 [..............................] - ETA: 0s - loss: 0.6238 - mse: 0.6238
2300/3021 [=====================>........] - ETA: 0s - loss: 0.7615 - mse: 0.7615
3021/3021 [==============================] - 0s 149us/sample - loss: 0.7303 - mse: 0.7303 - val_loss: 0.0973 - val_mse: 0.0973
Epoch 42/100
100/3021 [..............................] - ETA: 0s - loss: 0.6766 - mse: 0.6766
1500/3021 [=============>................] - ETA: 0s - loss: 0.7010 - mse: 0.7010
3021/3021 [==============================] - 1s 168us/sample - loss: 0.7077 - mse: 0.7077 - val_loss: 0.1093 - val_mse: 0.1093
Epoch 43/100
100/3021 [..............................] - ETA: 0s - loss: 0.8048 - mse: 0.8048
2000/3021 [==================>...........] - ETA: 0s - loss: 0.7118 - mse: 0.7118
3021/3021 [==============================] - 0s 163us/sample - loss: 0.7051 - mse: 0.7051 - val_loss: 0.1081 - val_mse: 0.1081
Epoch 44/100
100/3021 [..............................] - ETA: 0s - loss: 0.9133 - mse: 0.9133
1900/3021 [=================>............] - ETA: 0s - loss: 0.7806 - mse: 0.7806
3021/3021 [==============================] - 0s 157us/sample - loss: 0.7550 - mse: 0.7550 - val_loss: 0.0979 - val_mse: 0.0979
Epoch 45/100
100/3021 [..............................] - ETA: 0s - loss: 0.6488 - mse: 0.6488
1500/3021 [=============>................] - ETA: 0s - loss: 0.7052 - mse: 0.7052
3021/3021 [==============================] - 0s 153us/sample - loss: 0.6882 - mse: 0.6882 - val_loss: 0.0977 - val_mse: 0.0977
Epoch 46/100
100/3021 [..............................] - ETA: 0s - loss: 0.9164 - mse: 0.9164
1200/3021 [==========>...................] - ETA: 0s - loss: 0.6583 - mse: 0.6583
3021/3021 [==============================] - 1s 168us/sample - loss: 0.6822 - mse: 0.6822 - val_loss: 0.0869 - val_mse: 0.0869
Epoch 47/100
100/3021 [..............................] - ETA: 0s - loss: 0.7681 - mse: 0.7681
1800/3021 [================>.............] - ETA: 0s - loss: 0.6909 - mse: 0.6909
3021/3021 [==============================] - 0s 151us/sample - loss: 0.6924 - mse: 0.6924 - val_loss: 0.0794 - val_mse: 0.0794
Epoch 48/100
100/3021 [..............................] - ETA: 0s - loss: 0.5250 - mse: 0.5250
2300/3021 [=====================>........] - ETA: 0s - loss: 0.6500 - mse: 0.6500
3021/3021 [==============================] - 0s 155us/sample - loss: 0.6528 - mse: 0.6528 - val_loss: 0.0897 - val_mse: 0.0897
Epoch 49/100
100/3021 [..............................] - ETA: 0s - loss: 0.7753 - mse: 0.7753
2300/3021 [=====================>........] - ETA: 0s - loss: 0.6526 - mse: 0.6526
3021/3021 [==============================] - 0s 150us/sample - loss: 0.6549 - mse: 0.6549 - val_loss: 0.0945 - val_mse: 0.0945
Epoch 50/100
100/3021 [..............................] - ETA: 0s - loss: 0.8524 - mse: 0.8524
900/3021 [=======>......................] - ETA: 0s - loss: 0.7432 - mse: 0.7432
3000/3021 [============================>.] - ETA: 0s - loss: 0.6933 - mse: 0.6933
3021/3021 [==============================] - 0s 162us/sample - loss: 0.6926 - mse: 0.6926 - val_loss: 0.0898 - val_mse: 0.0898
Epoch 51/100
100/3021 [..............................] - ETA: 0s - loss: 0.7756 - mse: 0.7756
1900/3021 [=================>............] - ETA: 0s - loss: 0.6840 - mse: 0.6840
3021/3021 [==============================] - 0s 162us/sample - loss: 0.6502 - mse: 0.6502 - val_loss: 0.0694 - val_mse: 0.0694
Epoch 52/100
100/3021 [..............................] - ETA: 0s - loss: 0.6403 - mse: 0.6403
1000/3021 [========>.....................] - ETA: 0s - loss: 0.6728 - mse: 0.6728
3021/3021 [==============================] - 0s 159us/sample - loss: 0.6825 - mse: 0.6825 - val_loss: 0.0762 - val_mse: 0.0762
Epoch 53/100
100/3021 [..............................] - ETA: 0s - loss: 0.6171 - mse: 0.6171
2200/3021 [====================>.........] - ETA: 0s - loss: 0.6292 - mse: 0.6292
3021/3021 [==============================] - 0s 151us/sample - loss: 0.6196 - mse: 0.6196 - val_loss: 0.0741 - val_mse: 0.0741
Epoch 54/100
100/3021 [..............................] - ETA: 0s - loss: 0.6657 - mse: 0.6657
1700/3021 [===============>..............] - ETA: 0s - loss: 0.6025 - mse: 0.6025
3021/3021 [==============================] - 0s 152us/sample - loss: 0.6150 - mse: 0.6150 - val_loss: 0.0938 - val_mse: 0.0938
Epoch 55/100
100/3021 [..............................] - ETA: 0s - loss: 0.4723 - mse: 0.4723
2300/3021 [=====================>........] - ETA: 0s - loss: 0.6632 - mse: 0.6632
3021/3021 [==============================] - 0s 153us/sample - loss: 0.6569 - mse: 0.6569 - val_loss: 0.0698 - val_mse: 0.0698
Epoch 56/100
100/3021 [..............................] - ETA: 0s - loss: 0.6961 - mse: 0.6961
2300/3021 [=====================>........] - ETA: 0s - loss: 0.5989 - mse: 0.5989
3021/3021 [==============================] - 0s 150us/sample - loss: 0.5971 - mse: 0.5971 - val_loss: 0.0815 - val_mse: 0.0815
Epoch 57/100
100/3021 [..............................] - ETA: 0s - loss: 0.7248 - mse: 0.7248
2300/3021 [=====================>........] - ETA: 0s - loss: 0.6221 - mse: 0.6221
3021/3021 [==============================] - 0s 153us/sample - loss: 0.6166 - mse: 0.6166 - val_loss: 0.0674 - val_mse: 0.0674
Epoch 58/100
100/3021 [..............................] - ETA: 0s - loss: 0.5194 - mse: 0.5194
1200/3021 [==========>...................] - ETA: 0s - loss: 0.6108 - mse: 0.6108
2600/3021 [========================>.....] - ETA: 0s - loss: 0.6038 - mse: 0.6038
3021/3021 [==============================] - 0s 165us/sample - loss: 0.6062 - mse: 0.6062 - val_loss: 0.0685 - val_mse: 0.0685
Epoch 59/100
100/3021 [..............................] - ETA: 0s - loss: 0.6743 - mse: 0.6743
1400/3021 [============>.................] - ETA: 0s - loss: 0.6254 - mse: 0.6254
3021/3021 [==============================] - 0s 162us/sample - loss: 0.6470 - mse: 0.6470 - val_loss: 0.0688 - val_mse: 0.0688
Epoch 60/100
100/3021 [..............................] - ETA: 0s - loss: 0.5484 - mse: 0.5484
1800/3021 [================>.............] - ETA: 0s - loss: 0.6022 - mse: 0.6022
3021/3021 [==============================] - 0s 159us/sample - loss: 0.6071 - mse: 0.6071 - val_loss: 0.0726 - val_mse: 0.0726
Epoch 61/100
100/3021 [..............................] - ETA: 0s - loss: 0.4851 - mse: 0.4851
1800/3021 [================>.............] - ETA: 0s - loss: 0.5905 - mse: 0.5905
3021/3021 [==============================] - 0s 151us/sample - loss: 0.6108 - mse: 0.6108 - val_loss: 0.0624 - val_mse: 0.0624
Epoch 62/100
100/3021 [..............................] - ETA: 0s - loss: 0.5679 - mse: 0.5679
2300/3021 [=====================>........] - ETA: 0s - loss: 0.5781 - mse: 0.5781
3021/3021 [==============================] - 0s 149us/sample - loss: 0.5702 - mse: 0.5702 - val_loss: 0.0689 - val_mse: 0.0689
Epoch 63/100
100/3021 [..............................] - ETA: 0s - loss: 0.4586 - mse: 0.4586
2400/3021 [======================>.......] - ETA: 0s - loss: 0.5810 - mse: 0.5810
3021/3021 [==============================] - 0s 164us/sample - loss: 0.5818 - mse: 0.5818 - val_loss: 0.0692 - val_mse: 0.0692
Epoch 64/100
100/3021 [..............................] - ETA: 0s - loss: 0.5784 - mse: 0.5784
1000/3021 [========>.....................] - ETA: 0s - loss: 0.5492 - mse: 0.5492
3000/3021 [============================>.] - ETA: 0s - loss: 0.5789 - mse: 0.5789
3021/3021 [==============================] - 1s 166us/sample - loss: 0.5783 - mse: 0.5783 - val_loss: 0.0584 - val_mse: 0.0584
Epoch 65/100
100/3021 [..............................] - ETA: 0s - loss: 0.6514 - mse: 0.6514
2300/3021 [=====================>........] - ETA: 0s - loss: 0.5990 - mse: 0.5990
3021/3021 [==============================] - 0s 157us/sample - loss: 0.5969 - mse: 0.5969 - val_loss: 0.0531 - val_mse: 0.0531
Epoch 66/100
100/3021 [..............................] - ETA: 0s - loss: 0.6677 - mse: 0.6677
1500/3021 [=============>................] - ETA: 0s - loss: 0.5363 - mse: 0.5363
3021/3021 [==============================] - 0s 156us/sample - loss: 0.5448 - mse: 0.5448 - val_loss: 0.0539 - val_mse: 0.0539
Epoch 67/100
100/3021 [..............................] - ETA: 0s - loss: 0.5918 - mse: 0.5918
1300/3021 [===========>..................] - ETA: 0s - loss: 0.5713 - mse: 0.5713
3021/3021 [==============================] - 1s 167us/sample - loss: 0.5705 - mse: 0.5705 - val_loss: 0.0734 - val_mse: 0.0734
Epoch 68/100
100/3021 [..............................] - ETA: 0s - loss: 0.5542 - mse: 0.5542
1800/3021 [================>.............] - ETA: 0s - loss: 0.5626 - mse: 0.5626
3021/3021 [==============================] - 0s 155us/sample - loss: 0.5717 - mse: 0.5717 - val_loss: 0.0491 - val_mse: 0.0491
Epoch 69/100
100/3021 [..............................] - ETA: 0s - loss: 0.4273 - mse: 0.4273
2300/3021 [=====================>........] - ETA: 0s - loss: 0.5411 - mse: 0.5411
3021/3021 [==============================] - 0s 150us/sample - loss: 0.5522 - mse: 0.5522 - val_loss: 0.0556 - val_mse: 0.0556
Epoch 70/100
100/3021 [..............................] - ETA: 0s - loss: 0.5972 - mse: 0.5972
2100/3021 [===================>..........] - ETA: 0s - loss: 0.5558 - mse: 0.5558
3021/3021 [==============================] - 1s 168us/sample - loss: 0.5524 - mse: 0.5524 - val_loss: 0.0612 - val_mse: 0.0612
Epoch 71/100
100/3021 [..............................] - ETA: 0s - loss: 0.5983 - mse: 0.5983
1400/3021 [============>.................] - ETA: 0s - loss: 0.5162 - mse: 0.5162
3021/3021 [==============================] - 1s 166us/sample - loss: 0.5393 - mse: 0.5393 - val_loss: 0.0711 - val_mse: 0.0711
Epoch 72/100
100/3021 [..............................] - ETA: 0s - loss: 0.6374 - mse: 0.6374
2000/3021 [==================>...........] - ETA: 0s - loss: 0.5599 - mse: 0.5599
3021/3021 [==============================] - 0s 165us/sample - loss: 0.5554 - mse: 0.5554 - val_loss: 0.0624 - val_mse: 0.0624
Epoch 73/100
100/3021 [..............................] - ETA: 0s - loss: 0.4456 - mse: 0.4456
1300/3021 [===========>..................] - ETA: 0s - loss: 0.5511 - mse: 0.5511
3021/3021 [==============================] - 0s 164us/sample - loss: 0.5540 - mse: 0.5540 - val_loss: 0.0617 - val_mse: 0.0617
Epoch 74/100
100/3021 [..............................] - ETA: 0s - loss: 0.6321 - mse: 0.6321
1600/3021 [==============>...............] - ETA: 0s - loss: 0.5537 - mse: 0.5537
3021/3021 [==============================] - 0s 162us/sample - loss: 0.5541 - mse: 0.5541 - val_loss: 0.0574 - val_mse: 0.0574
Epoch 75/100
100/3021 [..............................] - ETA: 0s - loss: 0.5032 - mse: 0.5032
2100/3021 [===================>..........] - ETA: 0s - loss: 0.5110 - mse: 0.5110
3021/3021 [==============================] - 0s 149us/sample - loss: 0.5302 - mse: 0.5302 - val_loss: 0.0583 - val_mse: 0.0583
Epoch 76/100
100/3021 [..............................] - ETA: 0s - loss: 0.5564 - mse: 0.5564
2400/3021 [======================>.......] - ETA: 0s - loss: 0.5216 - mse: 0.5216
3021/3021 [==============================] - 0s 155us/sample - loss: 0.5264 - mse: 0.5264 - val_loss: 0.0560 - val_mse: 0.0560
Epoch 77/100
100/3021 [..............................] - ETA: 0s - loss: 0.6115 - mse: 0.6115
2200/3021 [====================>.........] - ETA: 0s - loss: 0.5315 - mse: 0.5315
3021/3021 [==============================] - 0s 150us/sample - loss: 0.5426 - mse: 0.5426 - val_loss: 0.0576 - val_mse: 0.0576
Epoch 78/100
100/3021 [..............................] - ETA: 0s - loss: 0.3633 - mse: 0.3633
2000/3021 [==================>...........] - ETA: 0s - loss: 0.5112 - mse: 0.5112
3021/3021 [==============================] - 0s 163us/sample - loss: 0.5094 - mse: 0.5094 - val_loss: 0.0644 - val_mse: 0.0644
Epoch 79/100
100/3021 [..............................] - ETA: 0s - loss: 0.5238 - mse: 0.5238
1300/3021 [===========>..................] - ETA: 0s - loss: 0.5553 - mse: 0.5553
3021/3021 [==============================] - 0s 159us/sample - loss: 0.5373 - mse: 0.5373 - val_loss: 0.0579 - val_mse: 0.0579
Epoch 80/100
100/3021 [..............................] - ETA: 0s - loss: 0.5930 - mse: 0.5930
2300/3021 [=====================>........] - ETA: 0s - loss: 0.4888 - mse: 0.4888
3021/3021 [==============================] - 0s 156us/sample - loss: 0.5026 - mse: 0.5026 - val_loss: 0.0595 - val_mse: 0.0595
Epoch 81/100
100/3021 [..............................] - ETA: 0s - loss: 0.5579 - mse: 0.5579
1900/3021 [=================>............] - ETA: 0s - loss: 0.5134 - mse: 0.5134
3021/3021 [==============================] - 0s 152us/sample - loss: 0.5140 - mse: 0.5140 - val_loss: 0.0492 - val_mse: 0.0492
Epoch 82/100
100/3021 [..............................] - ETA: 0s - loss: 0.4581 - mse: 0.4581
2400/3021 [======================>.......] - ETA: 0s - loss: 0.5223 - mse: 0.5223
3021/3021 [==============================] - 0s 151us/sample - loss: 0.5199 - mse: 0.5199 - val_loss: 0.0558 - val_mse: 0.0558
Epoch 83/100
100/3021 [..............................] - ETA: 0s - loss: 0.5441 - mse: 0.5441
2500/3021 [=======================>......] - ETA: 0s - loss: 0.5141 - mse: 0.5141
3021/3021 [==============================] - 0s 147us/sample - loss: 0.5217 - mse: 0.5217 - val_loss: 0.0576 - val_mse: 0.0576
Epoch 84/100
100/3021 [..............................] - ETA: 0s - loss: 0.6567 - mse: 0.6567
1900/3021 [=================>............] - ETA: 0s - loss: 0.5431 - mse: 0.5431
3021/3021 [==============================] - 1s 269us/sample - loss: 0.5295 - mse: 0.5295 - val_loss: 0.0567 - val_mse: 0.0567
Epoch 85/100
100/3021 [..............................] - ETA: 0s - loss: 0.7080 - mse: 0.7080
1600/3021 [==============>...............] - ETA: 0s - loss: 0.5386 - mse: 0.5386
3021/3021 [==============================] - 0s 153us/sample - loss: 0.5288 - mse: 0.5288 - val_loss: 0.0511 - val_mse: 0.0511
Epoch 86/100
100/3021 [..............................] - ETA: 0s - loss: 0.5118 - mse: 0.5118
2400/3021 [======================>.......] - ETA: 0s - loss: 0.4867 - mse: 0.4867
3021/3021 [==============================] - 0s 142us/sample - loss: 0.4964 - mse: 0.4964 - val_loss: 0.0496 - val_mse: 0.0496
Epoch 87/100
100/3021 [..............................] - ETA: 0s - loss: 0.6427 - mse: 0.6427
2200/3021 [====================>.........] - ETA: 0s - loss: 0.4905 - mse: 0.4905
3021/3021 [==============================] - 0s 147us/sample - loss: 0.4847 - mse: 0.4847 - val_loss: 0.0454 - val_mse: 0.0454
Epoch 88/100
100/3021 [..............................] - ETA: 0s - loss: 0.5744 - mse: 0.5744
2300/3021 [=====================>........] - ETA: 0s - loss: 0.4864 - mse: 0.4864
3021/3021 [==============================] - 0s 157us/sample - loss: 0.4888 - mse: 0.4888 - val_loss: 0.0571 - val_mse: 0.0571
Epoch 89/100
100/3021 [..............................] - ETA: 0s - loss: 0.4362 - mse: 0.4362
1700/3021 [===============>..............] - ETA: 0s - loss: 0.5009 - mse: 0.5009
3021/3021 [==============================] - 0s 159us/sample - loss: 0.4999 - mse: 0.4999 - val_loss: 0.0485 - val_mse: 0.0485
Epoch 90/100
100/3021 [..............................] - ETA: 0s - loss: 0.4526 - mse: 0.4526
2300/3021 [=====================>........] - ETA: 0s - loss: 0.4926 - mse: 0.4926
3021/3021 [==============================] - 0s 151us/sample - loss: 0.5005 - mse: 0.5005 - val_loss: 0.0560 - val_mse: 0.0560
Epoch 91/100
100/3021 [..............................] - ETA: 0s - loss: 0.3590 - mse: 0.3590
2300/3021 [=====================>........] - ETA: 0s - loss: 0.4809 - mse: 0.4809
3021/3021 [==============================] - 0s 146us/sample - loss: 0.4761 - mse: 0.4761 - val_loss: 0.0479 - val_mse: 0.0479
Epoch 92/100
100/3021 [..............................] - ETA: 0s - loss: 0.4466 - mse: 0.4466
1600/3021 [==============>...............] - ETA: 0s - loss: 0.4730 - mse: 0.4730
3021/3021 [==============================] - 0s 154us/sample - loss: 0.4842 - mse: 0.4842 - val_loss: 0.0608 - val_mse: 0.0608
Epoch 93/100
100/3021 [..............................] - ETA: 0s - loss: 0.6451 - mse: 0.6451
2200/3021 [====================>.........] - ETA: 0s - loss: 0.5076 - mse: 0.5076
3021/3021 [==============================] - 0s 150us/sample - loss: 0.5066 - mse: 0.5066 - val_loss: 0.0519 - val_mse: 0.0519
Epoch 94/100
100/3021 [..............................] - ETA: 0s - loss: 0.3738 - mse: 0.3738
1400/3021 [============>.................] - ETA: 0s - loss: 0.4654 - mse: 0.4654
3021/3021 [==============================] - 1s 170us/sample - loss: 0.4762 - mse: 0.4762 - val_loss: 0.0430 - val_mse: 0.0430
Epoch 95/100
100/3021 [..............................] - ETA: 0s - loss: 0.4172 - mse: 0.4172
1600/3021 [==============>...............] - ETA: 0s - loss: 0.4788 - mse: 0.4788
3021/3021 [==============================] - 1s 170us/sample - loss: 0.4877 - mse: 0.4877 - val_loss: 0.0475 - val_mse: 0.0475
Epoch 96/100
100/3021 [..............................] - ETA: 0s - loss: 0.4693 - mse: 0.4693
1800/3021 [================>.............] - ETA: 0s - loss: 0.5021 - mse: 0.5021
3021/3021 [==============================] - 0s 158us/sample - loss: 0.4921 - mse: 0.4921 - val_loss: 0.0492 - val_mse: 0.0492
Epoch 97/100
100/3021 [..............................] - ETA: 0s - loss: 0.3690 - mse: 0.3690
1600/3021 [==============>...............] - ETA: 0s - loss: 0.4847 - mse: 0.4847
3021/3021 [==============================] - 0s 156us/sample - loss: 0.4749 - mse: 0.4749 - val_loss: 0.0458 - val_mse: 0.0458
Epoch 98/100
100/3021 [..............................] - ETA: 0s - loss: 0.4214 - mse: 0.4214
1400/3021 [============>.................] - ETA: 0s - loss: 0.4791 - mse: 0.4791
3021/3021 [==============================] - 1s 174us/sample - loss: 0.4625 - mse: 0.4625 - val_loss: 0.0477 - val_mse: 0.0477
Epoch 99/100
100/3021 [..............................] - ETA: 0s - loss: 0.3547 - mse: 0.3547
800/3021 [======>.......................] - ETA: 0s - loss: 0.4330 - mse: 0.4330
2700/3021 [=========================>....] - ETA: 0s - loss: 0.4539 - mse: 0.4539
3021/3021 [==============================] - 0s 159us/sample - loss: 0.4518 - mse: 0.4518 - val_loss: 0.0642 - val_mse: 0.0642
Epoch 100/100
100/3021 [..............................] - ETA: 0s - loss: 0.4837 - mse: 0.4837
2400/3021 [======================>.......] - ETA: 0s - loss: 0.4701 - mse: 0.4701
3021/3021 [==============================] - 0s 155us/sample - loss: 0.4664 - mse: 0.4664 - val_loss: 0.0490 - val_mse: 0.0490Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-05-04T00-56-08Z
Training run 10/46 (flags = list(392, 128, 1e-04, 500, 100, "relu", "tanh", 0.1, 0.2))
Using run directory runs/2020-05-04T00-57-00Z
> FLAGS <- flags(
+ flag_numeric("nodes1", 128),
+ flag_numeric("nodes2", 128),
+ flag_numeric("batch_size", 100),
+ flag_string("activation1" .... [TRUNCATED]
> model = keras_model_sequential()
> model %>%
+ layer_dense(units=FLAGS$nodes1, activation=FLAGS$activation1, input_shape=dim(efw_train2)[2]) %>%
+ layer_dropout(FLAGS$dropout1) %> .... [TRUNCATED]
> model %>% compile(
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ loss = 'mse',
+ metrics = c('mse')
+ )
> model %>% fit(
+ as.matrix(efw_train2), train2Label,
+ epochs=FLAGS$epochs,
+ batch_size=FLAGS$batch_size,
+ validation_data=list(as.matrix( .... [TRUNCATED]
Train on 3021 samples, validate on 334 samples
Epoch 1/100
500/3021 [===>..........................] - ETA: 1s - loss: 38.8375 - mse: 38.8375
3021/3021 [==============================] - 2s 559us/sample - loss: 39.0807 - mse: 39.0807 - val_loss: 38.1828 - val_mse: 38.1828
Epoch 2/100
500/3021 [===>..........................] - ETA: 0s - loss: 38.0055 - mse: 38.0055
3021/3021 [==============================] - 0s 152us/sample - loss: 37.6866 - mse: 37.6866 - val_loss: 36.8643 - val_mse: 36.8643
Epoch 3/100
500/3021 [===>..........................] - ETA: 0s - loss: 36.1395 - mse: 36.1395
3021/3021 [==============================] - 0s 162us/sample - loss: 36.3642 - mse: 36.3642 - val_loss: 35.5884 - val_mse: 35.5884
Epoch 4/100
500/3021 [===>..........................] - ETA: 0s - loss: 35.4583 - mse: 35.4583
3021/3021 [==============================] - 0s 153us/sample - loss: 35.1376 - mse: 35.1376 - val_loss: 34.3502 - val_mse: 34.3502
Epoch 5/100
500/3021 [===>..........................] - ETA: 0s - loss: 34.2677 - mse: 34.2677
3021/3021 [==============================] - 0s 146us/sample - loss: 33.9046 - mse: 33.9046 - val_loss: 33.1376 - val_mse: 33.1376
Epoch 6/100
500/3021 [===>..........................] - ETA: 0s - loss: 33.6718 - mse: 33.6718
3000/3021 [============================>.] - ETA: 0s - loss: 32.7047 - mse: 32.7047
3021/3021 [==============================] - 0s 148us/sample - loss: 32.6946 - mse: 32.6946 - val_loss: 31.9616 - val_mse: 31.9616
Epoch 7/100
500/3021 [===>..........................] - ETA: 0s - loss: 32.2443 - mse: 32.2443
3021/3021 [==============================] - 0s 144us/sample - loss: 31.5215 - mse: 31.5215 - val_loss: 30.8240 - val_mse: 30.8240
Epoch 8/100
500/3021 [===>..........................] - ETA: 0s - loss: 31.1465 - mse: 31.1465
3021/3021 [==============================] - 0s 154us/sample - loss: 30.4061 - mse: 30.4061 - val_loss: 29.7181 - val_mse: 29.7181
Epoch 9/100
500/3021 [===>..........................] - ETA: 0s - loss: 29.8615 - mse: 29.8615
3021/3021 [==============================] - 0s 145us/sample - loss: 29.3175 - mse: 29.3175 - val_loss: 28.6490 - val_mse: 28.6490
Epoch 10/100
500/3021 [===>..........................] - ETA: 0s - loss: 28.0198 - mse: 28.0198
3021/3021 [==============================] - 0s 149us/sample - loss: 28.2728 - mse: 28.2728 - val_loss: 27.6104 - val_mse: 27.6104
Epoch 11/100
500/3021 [===>..........................] - ETA: 0s - loss: 28.0998 - mse: 28.0998
3021/3021 [==============================] - 0s 142us/sample - loss: 27.2455 - mse: 27.2455 - val_loss: 26.6100 - val_mse: 26.6100
Epoch 12/100
500/3021 [===>..........................] - ETA: 0s - loss: 26.7014 - mse: 26.7014
3021/3021 [==============================] - 0s 149us/sample - loss: 26.2849 - mse: 26.2849 - val_loss: 25.6355 - val_mse: 25.6355
Epoch 13/100
500/3021 [===>..........................] - ETA: 0s - loss: 25.8384 - mse: 25.8384
3021/3021 [==============================] - 0s 148us/sample - loss: 25.2608 - mse: 25.2608 - val_loss: 24.6972 - val_mse: 24.6972
Epoch 14/100
500/3021 [===>..........................] - ETA: 0s - loss: 24.3750 - mse: 24.3750
3021/3021 [==============================] - 0s 145us/sample - loss: 24.3779 - mse: 24.3779 - val_loss: 23.7870 - val_mse: 23.7870
Epoch 15/100
500/3021 [===>..........................] - ETA: 0s - loss: 23.2547 - mse: 23.2547
3021/3021 [==============================] - 0s 141us/sample - loss: 23.4737 - mse: 23.4737 - val_loss: 22.8988 - val_mse: 22.8988
Epoch 16/100
500/3021 [===>..........................] - ETA: 0s - loss: 22.5080 - mse: 22.5080
3021/3021 [==============================] - 0s 147us/sample - loss: 22.6363 - mse: 22.6363 - val_loss: 22.0462 - val_mse: 22.0462
Epoch 17/100
500/3021 [===>..........................] - ETA: 0s - loss: 21.5092 - mse: 21.5092
3021/3021 [==============================] - 0s 137us/sample - loss: 21.7912 - mse: 21.7912 - val_loss: 21.2160 - val_mse: 21.2160
Epoch 18/100
500/3021 [===>..........................] - ETA: 0s - loss: 21.1616 - mse: 21.1616
3021/3021 [==============================] - 0s 151us/sample - loss: 20.9496 - mse: 20.9496 - val_loss: 20.4235 - val_mse: 20.4235
Epoch 19/100
500/3021 [===>..........................] - ETA: 0s - loss: 20.7918 - mse: 20.7918
3021/3021 [==============================] - 0s 164us/sample - loss: 20.1805 - mse: 20.1805 - val_loss: 19.6690 - val_mse: 19.6690
Epoch 20/100
500/3021 [===>..........................] - ETA: 0s - loss: 20.4261 - mse: 20.4261
3021/3021 [==============================] - 0s 142us/sample - loss: 19.4500 - mse: 19.4500 - val_loss: 18.9316 - val_mse: 18.9316
Epoch 21/100
500/3021 [===>..........................] - ETA: 0s - loss: 19.4485 - mse: 19.4485
3021/3021 [==============================] - 0s 147us/sample - loss: 18.7232 - mse: 18.7232 - val_loss: 18.2183 - val_mse: 18.2183
Epoch 22/100
500/3021 [===>..........................] - ETA: 0s - loss: 17.9651 - mse: 17.9651
3021/3021 [==============================] - 0s 148us/sample - loss: 18.0311 - mse: 18.0311 - val_loss: 17.5436 - val_mse: 17.5436
Epoch 23/100
500/3021 [===>..........................] - ETA: 0s - loss: 17.2298 - mse: 17.2298
3021/3021 [==============================] - 0s 143us/sample - loss: 17.4059 - mse: 17.4059 - val_loss: 16.8969 - val_mse: 16.8969
Epoch 24/100
500/3021 [===>..........................] - ETA: 0s - loss: 17.2069 - mse: 17.2069
3021/3021 [==============================] - 0s 143us/sample - loss: 16.7638 - mse: 16.7638 - val_loss: 16.2806 - val_mse: 16.2806
Epoch 25/100
500/3021 [===>..........................] - ETA: 0s - loss: 16.6307 - mse: 16.6307
3021/3021 [==============================] - 0s 147us/sample - loss: 16.1726 - mse: 16.1726 - val_loss: 15.6945 - val_mse: 15.6945
Epoch 26/100
500/3021 [===>..........................] - ETA: 0s - loss: 15.7759 - mse: 15.7759
3021/3021 [==============================] - 0s 139us/sample - loss: 15.6325 - mse: 15.6325 - val_loss: 15.1324 - val_mse: 15.1324
Epoch 27/100
500/3021 [===>..........................] - ETA: 0s - loss: 15.1535 - mse: 15.1535
3021/3021 [==============================] - 0s 140us/sample - loss: 15.0606 - mse: 15.0606 - val_loss: 14.6076 - val_mse: 14.6076
Epoch 28/100
500/3021 [===>..........................] - ETA: 0s - loss: 14.6656 - mse: 14.6656
3021/3021 [==============================] - 0s 146us/sample - loss: 14.5369 - mse: 14.5369 - val_loss: 14.1083 - val_mse: 14.1083
Epoch 29/100
500/3021 [===>..........................] - ETA: 0s - loss: 13.8992 - mse: 13.8992
3021/3021 [==============================] - 0s 141us/sample - loss: 14.0734 - mse: 14.0734 - val_loss: 13.6296 - val_mse: 13.6296
Epoch 30/100
500/3021 [===>..........................] - ETA: 0s - loss: 13.3795 - mse: 13.3795
3021/3021 [==============================] - 0s 136us/sample - loss: 13.6231 - mse: 13.6231 - val_loss: 13.1794 - val_mse: 13.1794
Epoch 31/100
500/3021 [===>..........................] - ETA: 0s - loss: 12.5848 - mse: 12.5848
3021/3021 [==============================] - 0s 138us/sample - loss: 13.1682 - mse: 13.1682 - val_loss: 12.7573 - val_mse: 12.7573
Epoch 32/100
500/3021 [===>..........................] - ETA: 0s - loss: 12.5595 - mse: 12.5595
3021/3021 [==============================] - 0s 140us/sample - loss: 12.7770 - mse: 12.7770 - val_loss: 12.3575 - val_mse: 12.3575
Epoch 33/100
500/3021 [===>..........................] - ETA: 0s - loss: 12.1929 - mse: 12.1929
3021/3021 [==============================] - 0s 146us/sample - loss: 12.3797 - mse: 12.3797 - val_loss: 11.9772 - val_mse: 11.9772
Epoch 34/100
500/3021 [===>..........................] - ETA: 0s - loss: 11.9490 - mse: 11.9490
3021/3021 [==============================] - 0s 148us/sample - loss: 11.9940 - mse: 11.9940 - val_loss: 11.6105 - val_mse: 11.6105
Epoch 35/100
500/3021 [===>..........................] - ETA: 0s - loss: 11.1576 - mse: 11.1576
3021/3021 [==============================] - 0s 143us/sample - loss: 11.6632 - mse: 11.6632 - val_loss: 11.2533 - val_mse: 11.2533
Epoch 36/100
500/3021 [===>..........................] - ETA: 0s - loss: 11.6597 - mse: 11.6597
3021/3021 [==============================] - 0s 142us/sample - loss: 11.3102 - mse: 11.3102 - val_loss: 10.9104 - val_mse: 10.9104
Epoch 37/100
500/3021 [===>..........................] - ETA: 0s - loss: 11.9821 - mse: 11.9821
3021/3021 [==============================] - 0s 148us/sample - loss: 10.9515 - mse: 10.9515 - val_loss: 10.5865 - val_mse: 10.5865
Epoch 38/100
500/3021 [===>..........................] - ETA: 0s - loss: 10.9272 - mse: 10.9272
3021/3021 [==============================] - 0s 144us/sample - loss: 10.6549 - mse: 10.6549 - val_loss: 10.2832 - val_mse: 10.2832
Epoch 39/100
500/3021 [===>..........................] - ETA: 0s - loss: 10.3599 - mse: 10.3599
3021/3021 [==============================] - 0s 146us/sample - loss: 10.3923 - mse: 10.3923 - val_loss: 9.9913 - val_mse: 9.9913
Epoch 40/100
500/3021 [===>..........................] - ETA: 0s - loss: 9.7717 - mse: 9.7717
3021/3021 [==============================] - 0s 140us/sample - loss: 10.0566 - mse: 10.0566 - val_loss: 9.7109 - val_mse: 9.7109
Epoch 41/100
500/3021 [===>..........................] - ETA: 0s - loss: 9.6478 - mse: 9.6478
3021/3021 [==============================] - 0s 135us/sample - loss: 9.7855 - mse: 9.7855 - val_loss: 9.4407 - val_mse: 9.4407
Epoch 42/100
500/3021 [===>..........................] - ETA: 0s - loss: 9.4908 - mse: 9.4908
3021/3021 [==============================] - 0s 147us/sample - loss: 9.5264 - mse: 9.5264 - val_loss: 9.1827 - val_mse: 9.1827
Epoch 43/100
500/3021 [===>..........................] - ETA: 0s - loss: 9.3841 - mse: 9.3841
3021/3021 [==============================] - 0s 144us/sample - loss: 9.2952 - mse: 9.2952 - val_loss: 8.9391 - val_mse: 8.9391
Epoch 44/100
500/3021 [===>..........................] - ETA: 0s - loss: 10.2782 - mse: 10.2782
3021/3021 [==============================] - 0s 143us/sample - loss: 9.0340 - mse: 9.0340 - val_loss: 8.7052 - val_mse: 8.7052
Epoch 45/100
500/3021 [===>..........................] - ETA: 0s - loss: 8.7676 - mse: 8.7676
3021/3021 [==============================] - 0s 142us/sample - loss: 8.8431 - mse: 8.8431 - val_loss: 8.4791 - val_mse: 8.4791
Epoch 46/100
500/3021 [===>..........................] - ETA: 0s - loss: 8.4613 - mse: 8.4613
3021/3021 [==============================] - 0s 147us/sample - loss: 8.5996 - mse: 8.5996 - val_loss: 8.2579 - val_mse: 8.2579
Epoch 47/100
500/3021 [===>..........................] - ETA: 0s - loss: 8.1642 - mse: 8.1642
3021/3021 [==============================] - 0s 151us/sample - loss: 8.3949 - mse: 8.3949 - val_loss: 8.0441 - val_mse: 8.0441
Epoch 48/100
500/3021 [===>..........................] - ETA: 0s - loss: 8.4818 - mse: 8.4818
3021/3021 [==============================] - 0s 143us/sample - loss: 8.2014 - mse: 8.2014 - val_loss: 7.8373 - val_mse: 7.8373
Epoch 49/100
500/3021 [===>..........................] - ETA: 0s - loss: 7.8423 - mse: 7.8423
3021/3021 [==============================] - 0s 141us/sample - loss: 7.9773 - mse: 7.9773 - val_loss: 7.6373 - val_mse: 7.6373
Epoch 50/100
500/3021 [===>..........................] - ETA: 0s - loss: 7.5186 - mse: 7.5186
3021/3021 [==============================] - 0s 145us/sample - loss: 7.7936 - mse: 7.7936 - val_loss: 7.4436 - val_mse: 7.4436
Epoch 51/100
500/3021 [===>..........................] - ETA: 0s - loss: 7.4144 - mse: 7.4144
3021/3021 [==============================] - 0s 146us/sample - loss: 7.6027 - mse: 7.6027 - val_loss: 7.2569 - val_mse: 7.2569
Epoch 52/100
500/3021 [===>..........................] - ETA: 0s - loss: 7.3709 - mse: 7.3709
3021/3021 [==============================] - 0s 148us/sample - loss: 7.4005 - mse: 7.4005 - val_loss: 7.0792 - val_mse: 7.0792
Epoch 53/100
500/3021 [===>..........................] - ETA: 0s - loss: 7.6248 - mse: 7.6248
3021/3021 [==============================] - 0s 135us/sample - loss: 7.2404 - mse: 7.2404 - val_loss: 6.9064 - val_mse: 6.9064
Epoch 54/100
500/3021 [===>..........................] - ETA: 0s - loss: 6.9245 - mse: 6.9245
3021/3021 [==============================] - 0s 138us/sample - loss: 7.0602 - mse: 7.0602 - val_loss: 6.7361 - val_mse: 6.7361
Epoch 55/100
500/3021 [===>..........................] - ETA: 0s - loss: 7.1013 - mse: 7.1013
3021/3021 [==============================] - 0s 143us/sample - loss: 6.8530 - mse: 6.8530 - val_loss: 6.5712 - val_mse: 6.5712
Epoch 56/100
500/3021 [===>..........................] - ETA: 0s - loss: 6.5528 - mse: 6.5528
3021/3021 [==============================] - 0s 146us/sample - loss: 6.7390 - mse: 6.7390 - val_loss: 6.4110 - val_mse: 6.4110
Epoch 57/100
500/3021 [===>..........................] - ETA: 0s - loss: 6.6966 - mse: 6.6966
3021/3021 [==============================] - 0s 138us/sample - loss: 6.5592 - mse: 6.5592 - val_loss: 6.2550 - val_mse: 6.2550
Epoch 58/100
500/3021 [===>..........................] - ETA: 0s - loss: 6.8466 - mse: 6.8466
3021/3021 [==============================] - 0s 149us/sample - loss: 6.4031 - mse: 6.4031 - val_loss: 6.0995 - val_mse: 6.0995
Epoch 59/100
500/3021 [===>..........................] - ETA: 0s - loss: 6.4279 - mse: 6.4279
3021/3021 [==============================] - 0s 149us/sample - loss: 6.2680 - mse: 6.2680 - val_loss: 5.9499 - val_mse: 5.9499
Epoch 60/100
500/3021 [===>..........................] - ETA: 0s - loss: 6.4468 - mse: 6.4468
3021/3021 [==============================] - 0s 148us/sample - loss: 6.1079 - mse: 6.1079 - val_loss: 5.8060 - val_mse: 5.8060
Epoch 61/100
500/3021 [===>..........................] - ETA: 0s - loss: 5.9550 - mse: 5.9550
3021/3021 [==============================] - 0s 139us/sample - loss: 5.9713 - mse: 5.9713 - val_loss: 5.6680 - val_mse: 5.6680
Epoch 62/100
500/3021 [===>..........................] - ETA: 0s - loss: 5.8190 - mse: 5.8190
3021/3021 [==============================] - 0s 145us/sample - loss: 5.8286 - mse: 5.8286 - val_loss: 5.5296 - val_mse: 5.5296
Epoch 63/100
500/3021 [===>..........................] - ETA: 0s - loss: 6.1926 - mse: 6.1926
3021/3021 [==============================] - 0s 139us/sample - loss: 5.7017 - mse: 5.7017 - val_loss: 5.3918 - val_mse: 5.3918
Epoch 64/100
500/3021 [===>..........................] - ETA: 0s - loss: 5.8242 - mse: 5.8242
3021/3021 [==============================] - 0s 140us/sample - loss: 5.5554 - mse: 5.5554 - val_loss: 5.2556 - val_mse: 5.2556
Epoch 65/100
500/3021 [===>..........................] - ETA: 0s - loss: 5.1156 - mse: 5.1156
3021/3021 [==============================] - 0s 149us/sample - loss: 5.4159 - mse: 5.4159 - val_loss: 5.1285 - val_mse: 5.1285
Epoch 66/100
500/3021 [===>..........................] - ETA: 0s - loss: 5.3383 - mse: 5.3383
3021/3021 [==============================] - 0s 145us/sample - loss: 5.2920 - mse: 5.2920 - val_loss: 5.0021 - val_mse: 5.0021
Epoch 67/100
500/3021 [===>..........................] - ETA: 0s - loss: 4.9103 - mse: 4.9103
3021/3021 [==============================] - 0s 139us/sample - loss: 5.1463 - mse: 5.1463 - val_loss: 4.8802 - val_mse: 4.8802
Epoch 68/100
500/3021 [===>..........................] - ETA: 0s - loss: 5.3010 - mse: 5.3010
3021/3021 [==============================] - 0s 141us/sample - loss: 5.0380 - mse: 5.0380 - val_loss: 4.7642 - val_mse: 4.7642
Epoch 69/100
500/3021 [===>..........................] - ETA: 0s - loss: 4.6764 - mse: 4.6764
3021/3021 [==============================] - 0s 158us/sample - loss: 4.9150 - mse: 4.9150 - val_loss: 4.6517 - val_mse: 4.6517
Epoch 70/100
500/3021 [===>..........................] - ETA: 0s - loss: 5.2058 - mse: 5.2058
3021/3021 [==============================] - 0s 154us/sample - loss: 4.7987 - mse: 4.7987 - val_loss: 4.5407 - val_mse: 4.5407
Epoch 71/100
500/3021 [===>..........................] - ETA: 0s - loss: 4.0114 - mse: 4.0114
3021/3021 [==============================] - 0s 143us/sample - loss: 4.6797 - mse: 4.6797 - val_loss: 4.4345 - val_mse: 4.4345
Epoch 72/100
500/3021 [===>..........................] - ETA: 0s - loss: 4.5719 - mse: 4.5719
3021/3021 [==============================] - 0s 142us/sample - loss: 4.5623 - mse: 4.5623 - val_loss: 4.3320 - val_mse: 4.3320
Epoch 73/100
500/3021 [===>..........................] - ETA: 0s - loss: 4.6095 - mse: 4.6095
3021/3021 [==============================] - 0s 142us/sample - loss: 4.4878 - mse: 4.4878 - val_loss: 4.2293 - val_mse: 4.2293
Epoch 74/100
500/3021 [===>..........................] - ETA: 0s - loss: 4.6466 - mse: 4.6466
3021/3021 [==============================] - 0s 149us/sample - loss: 4.3891 - mse: 4.3891 - val_loss: 4.1290 - val_mse: 4.1290
Epoch 75/100
500/3021 [===>..........................] - ETA: 0s - loss: 4.1058 - mse: 4.1058
3021/3021 [==============================] - 0s 150us/sample - loss: 4.2800 - mse: 4.2800 - val_loss: 4.0334 - val_mse: 4.0334
Epoch 76/100
500/3021 [===>..........................] - ETA: 0s - loss: 4.2791 - mse: 4.2791
3021/3021 [==============================] - 0s 140us/sample - loss: 4.1781 - mse: 4.1781 - val_loss: 3.9400 - val_mse: 3.9400
Epoch 77/100
500/3021 [===>..........................] - ETA: 0s - loss: 4.0275 - mse: 4.0275
3021/3021 [==============================] - 0s 143us/sample - loss: 4.0683 - mse: 4.0683 - val_loss: 3.8487 - val_mse: 3.8487
Epoch 78/100
500/3021 [===>..........................] - ETA: 0s - loss: 4.0676 - mse: 4.0676
3021/3021 [==============================] - 0s 144us/sample - loss: 3.9993 - mse: 3.9993 - val_loss: 3.7609 - val_mse: 3.7609
Epoch 79/100
500/3021 [===>..........................] - ETA: 0s - loss: 3.9476 - mse: 3.9476
3021/3021 [==============================] - 0s 144us/sample - loss: 3.9031 - mse: 3.9031 - val_loss: 3.6766 - val_mse: 3.6766
Epoch 80/100
500/3021 [===>..........................] - ETA: 0s - loss: 3.7992 - mse: 3.7992
3021/3021 [==============================] - 0s 139us/sample - loss: 3.8148 - mse: 3.8148 - val_loss: 3.5949 - val_mse: 3.5949
Epoch 81/100
500/3021 [===>..........................] - ETA: 0s - loss: 4.0292 - mse: 4.0292
3021/3021 [==============================] - 0s 135us/sample - loss: 3.6919 - mse: 3.6919 - val_loss: 3.5130 - val_mse: 3.5130
Epoch 82/100
500/3021 [===>..........................] - ETA: 0s - loss: 3.7073 - mse: 3.7073
3021/3021 [==============================] - 0s 144us/sample - loss: 3.6255 - mse: 3.6255 - val_loss: 3.4317 - val_mse: 3.4317
Epoch 83/100
500/3021 [===>..........................] - ETA: 0s - loss: 3.7462 - mse: 3.7462
3021/3021 [==============================] - 0s 146us/sample - loss: 3.5185 - mse: 3.5185 - val_loss: 3.3522 - val_mse: 3.3522
Epoch 84/100
500/3021 [===>..........................] - ETA: 0s - loss: 3.4971 - mse: 3.4971
3021/3021 [==============================] - 0s 140us/sample - loss: 3.4510 - mse: 3.4510 - val_loss: 3.2762 - val_mse: 3.2762
Epoch 85/100
500/3021 [===>..........................] - ETA: 0s - loss: 3.1771 - mse: 3.1771
3021/3021 [==============================] - 0s 147us/sample - loss: 3.3833 - mse: 3.3833 - val_loss: 3.2026 - val_mse: 3.2026
Epoch 86/100
500/3021 [===>..........................] - ETA: 0s - loss: 3.0654 - mse: 3.0654
3021/3021 [==============================] - 0s 145us/sample - loss: 3.2926 - mse: 3.2926 - val_loss: 3.1313 - val_mse: 3.1313
Epoch 87/100
500/3021 [===>..........................] - ETA: 0s - loss: 3.2842 - mse: 3.2842
3021/3021 [==============================] - 0s 138us/sample - loss: 3.2323 - mse: 3.2323 - val_loss: 3.0618 - val_mse: 3.0618
Epoch 88/100
500/3021 [===>..........................] - ETA: 0s - loss: 3.2415 - mse: 3.2415
3021/3021 [==============================] - 0s 153us/sample - loss: 3.1696 - mse: 3.1696 - val_loss: 2.9933 - val_mse: 2.9933
Epoch 89/100
500/3021 [===>..........................] - ETA: 0s - loss: 3.1848 - mse: 3.1848
3021/3021 [==============================] - 0s 150us/sample - loss: 3.0869 - mse: 3.0869 - val_loss: 2.9276 - val_mse: 2.9276
Epoch 90/100
500/3021 [===>..........................] - ETA: 0s - loss: 3.2020 - mse: 3.2020
3021/3021 [==============================] - 0s 142us/sample - loss: 3.0139 - mse: 3.0139 - val_loss: 2.8632 - val_mse: 2.8632
Epoch 91/100
500/3021 [===>..........................] - ETA: 0s - loss: 2.8936 - mse: 2.8936
3021/3021 [==============================] - 0s 144us/sample - loss: 2.9235 - mse: 2.9235 - val_loss: 2.8006 - val_mse: 2.8006
Epoch 92/100
500/3021 [===>..........................] - ETA: 0s - loss: 2.8135 - mse: 2.8135
3021/3021 [==============================] - 0s 147us/sample - loss: 2.8644 - mse: 2.8644 - val_loss: 2.7397 - val_mse: 2.7397
Epoch 93/100
500/3021 [===>..........................] - ETA: 0s - loss: 2.8656 - mse: 2.8656
3021/3021 [==============================] - 0s 150us/sample - loss: 2.8044 - mse: 2.8044 - val_loss: 2.6788 - val_mse: 2.6788
Epoch 94/100
500/3021 [===>..........................] - ETA: 0s - loss: 2.7854 - mse: 2.7854
3021/3021 [==============================] - 0s 144us/sample - loss: 2.7433 - mse: 2.7433 - val_loss: 2.6185 - val_mse: 2.6185
Epoch 95/100
500/3021 [===>..........................] - ETA: 0s - loss: 2.6101 - mse: 2.6101
3021/3021 [==============================] - 0s 140us/sample - loss: 2.6925 - mse: 2.6925 - val_loss: 2.5582 - val_mse: 2.5582
Epoch 96/100
500/3021 [===>..........................] - ETA: 0s - loss: 2.5218 - mse: 2.5218
3021/3021 [==============================] - 0s 141us/sample - loss: 2.6275 - mse: 2.6275 - val_loss: 2.5002 - val_mse: 2.5002
Epoch 97/100
500/3021 [===>..........................] - ETA: 0s - loss: 2.5616 - mse: 2.5616
3021/3021 [==============================] - 0s 140us/sample - loss: 2.5812 - mse: 2.5812 - val_loss: 2.4436 - val_mse: 2.4436
Epoch 98/100
500/3021 [===>..........................] - ETA: 0s - loss: 2.5805 - mse: 2.5805
3021/3021 [==============================] - 0s 138us/sample - loss: 2.5103 - mse: 2.5103 - val_loss: 2.3872 - val_mse: 2.3872
Epoch 99/100
500/3021 [===>..........................] - ETA: 0s - loss: 2.4263 - mse: 2.4263
3021/3021 [==============================] - 0s 164us/sample - loss: 2.4420 - mse: 2.4420 - val_loss: 2.3330 - val_mse: 2.3330
Epoch 100/100
500/3021 [===>..........................] - ETA: 0s - loss: 2.1814 - mse: 2.1814
3021/3021 [==============================] - 0s 156us/sample - loss: 2.3890 - mse: 2.3890 - val_loss: 2.2811 - val_mse: 2.2811Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-05-04T00-57-00Z
Training run 11/46 (flags = list(392, 128, 0.01, 100, 50, "tanh", "sigmoid", 0.05, 0.2))
Using run directory runs/2020-05-04T00-57-48Z
> FLAGS <- flags(
+ flag_numeric("nodes1", 128),
+ flag_numeric("nodes2", 128),
+ flag_numeric("batch_size", 100),
+ flag_string("activation1" .... [TRUNCATED]
> model = keras_model_sequential()
> model %>%
+ layer_dense(units=FLAGS$nodes1, activation=FLAGS$activation1, input_shape=dim(efw_train2)[2]) %>%
+ layer_dropout(FLAGS$dropout1) %> .... [TRUNCATED]
> model %>% compile(
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ loss = 'mse',
+ metrics = c('mse')
+ )
> model %>% fit(
+ as.matrix(efw_train2), train2Label,
+ epochs=FLAGS$epochs,
+ batch_size=FLAGS$batch_size,
+ validation_data=list(as.matrix( .... [TRUNCATED]
Train on 3021 samples, validate on 334 samples
Epoch 1/50
100/3021 [..............................] - ETA: 6s - loss: 42.4779 - mse: 42.4779
1700/3021 [===============>..............] - ETA: 0s - loss: 15.0377 - mse: 15.0377
3000/3021 [============================>.] - ETA: 0s - loss: 9.3027 - mse: 9.3027
3021/3021 [==============================] - 1s 272us/sample - loss: 9.2433 - mse: 9.2433 - val_loss: 0.9019 - val_mse: 0.9019
Epoch 2/50
100/3021 [..............................] - ETA: 0s - loss: 0.8742 - mse: 0.8742
1400/3021 [============>.................] - ETA: 0s - loss: 0.7120 - mse: 0.7120
2800/3021 [==========================>...] - ETA: 0s - loss: 0.4806 - mse: 0.4806
3021/3021 [==============================] - 1s 175us/sample - loss: 0.4630 - mse: 0.4630 - val_loss: 0.1632 - val_mse: 0.1632
Epoch 3/50
100/3021 [..............................] - ETA: 0s - loss: 0.1594 - mse: 0.1594
1600/3021 [==============>...............] - ETA: 0s - loss: 0.1455 - mse: 0.1455
3000/3021 [============================>.] - ETA: 0s - loss: 0.1227 - mse: 0.1227
3021/3021 [==============================] - 1s 176us/sample - loss: 0.1222 - mse: 0.1222 - val_loss: 0.0794 - val_mse: 0.0794
Epoch 4/50
100/3021 [..............................] - ETA: 0s - loss: 0.0491 - mse: 0.0491
1200/3021 [==========>...................] - ETA: 0s - loss: 0.0866 - mse: 0.0866
2800/3021 [==========================>...] - ETA: 0s - loss: 0.0868 - mse: 0.0868
3021/3021 [==============================] - 1s 176us/sample - loss: 0.0859 - mse: 0.0859 - val_loss: 0.0689 - val_mse: 0.0689
Epoch 5/50
100/3021 [..............................] - ETA: 0s - loss: 0.0543 - mse: 0.0543
1700/3021 [===============>..............] - ETA: 0s - loss: 0.0684 - mse: 0.0684
3021/3021 [==============================] - 1s 168us/sample - loss: 0.0656 - mse: 0.0656 - val_loss: 0.0663 - val_mse: 0.0663
Epoch 6/50
100/3021 [..............................] - ETA: 0s - loss: 0.0796 - mse: 0.0796
1000/3021 [========>.....................] - ETA: 0s - loss: 0.0619 - mse: 0.0619
2800/3021 [==========================>...] - ETA: 0s - loss: 0.0618 - mse: 0.0618
3021/3021 [==============================] - 1s 172us/sample - loss: 0.0623 - mse: 0.0623 - val_loss: 0.0606 - val_mse: 0.0606
Epoch 7/50
100/3021 [..............................] - ETA: 0s - loss: 0.0445 - mse: 0.0445
1600/3021 [==============>...............] - ETA: 0s - loss: 0.0713 - mse: 0.0713
3021/3021 [==============================] - 1s 168us/sample - loss: 0.0657 - mse: 0.0657 - val_loss: 0.0521 - val_mse: 0.0521
Epoch 8/50
100/3021 [..............................] - ETA: 0s - loss: 0.0396 - mse: 0.0396
1200/3021 [==========>...................] - ETA: 0s - loss: 0.0530 - mse: 0.0530
3000/3021 [============================>.] - ETA: 0s - loss: 0.0600 - mse: 0.0600
3021/3021 [==============================] - 1s 169us/sample - loss: 0.0598 - mse: 0.0598 - val_loss: 0.0645 - val_mse: 0.0645
Epoch 9/50
100/3021 [..............................] - ETA: 0s - loss: 0.0451 - mse: 0.0451
1700/3021 [===============>..............] - ETA: 0s - loss: 0.0602 - mse: 0.0602
3021/3021 [==============================] - 1s 166us/sample - loss: 0.0644 - mse: 0.0644 - val_loss: 0.0703 - val_mse: 0.0703
Epoch 10/50
100/3021 [..............................] - ETA: 0s - loss: 0.0651 - mse: 0.0651
1600/3021 [==============>...............] - ETA: 0s - loss: 0.0541 - mse: 0.0541
3021/3021 [==============================] - 0s 164us/sample - loss: 0.0529 - mse: 0.0529 - val_loss: 0.0638 - val_mse: 0.0638
Epoch 11/50
100/3021 [..............................] - ETA: 0s - loss: 0.0535 - mse: 0.0535
1600/3021 [==============>...............] - ETA: 0s - loss: 0.0582 - mse: 0.0582
3021/3021 [==============================] - 1s 180us/sample - loss: 0.0581 - mse: 0.0581 - val_loss: 0.0710 - val_mse: 0.0710
Epoch 12/50
100/3021 [..............................] - ETA: 0s - loss: 0.0520 - mse: 0.0520
1400/3021 [============>.................] - ETA: 0s - loss: 0.0553 - mse: 0.0553
2800/3021 [==========================>...] - ETA: 0s - loss: 0.0603 - mse: 0.0603
3021/3021 [==============================] - 1s 179us/sample - loss: 0.0605 - mse: 0.0605 - val_loss: 0.0595 - val_mse: 0.0595
Epoch 13/50
100/3021 [..............................] - ETA: 0s - loss: 0.0511 - mse: 0.0511
1600/3021 [==============>...............] - ETA: 0s - loss: 0.0534 - mse: 0.0534
3000/3021 [============================>.] - ETA: 0s - loss: 0.0545 - mse: 0.0545
3021/3021 [==============================] - 1s 171us/sample - loss: 0.0547 - mse: 0.0547 - val_loss: 0.0506 - val_mse: 0.0506
Epoch 14/50
100/3021 [..............................] - ETA: 0s - loss: 0.0376 - mse: 0.0376
1100/3021 [=========>....................] - ETA: 0s - loss: 0.0657 - mse: 0.0657
2600/3021 [========================>.....] - ETA: 0s - loss: 0.0671 - mse: 0.0671
3021/3021 [==============================] - 1s 176us/sample - loss: 0.0661 - mse: 0.0661 - val_loss: 0.0777 - val_mse: 0.0777
Epoch 15/50
100/3021 [..............................] - ETA: 0s - loss: 0.0763 - mse: 0.0763
1500/3021 [=============>................] - ETA: 0s - loss: 0.0584 - mse: 0.0584
3000/3021 [============================>.] - ETA: 0s - loss: 0.0555 - mse: 0.0555
3021/3021 [==============================] - 1s 166us/sample - loss: 0.0554 - mse: 0.0554 - val_loss: 0.0480 - val_mse: 0.0480
Epoch 16/50
100/3021 [..............................] - ETA: 0s - loss: 0.0419 - mse: 0.0419
1300/3021 [===========>..................] - ETA: 0s - loss: 0.0526 - mse: 0.0526
2900/3021 [===========================>..] - ETA: 0s - loss: 0.0499 - mse: 0.0499
3021/3021 [==============================] - 1s 181us/sample - loss: 0.0502 - mse: 0.0502 - val_loss: 0.0625 - val_mse: 0.0625
Epoch 17/50
100/3021 [..............................] - ETA: 0s - loss: 0.0774 - mse: 0.0774
1000/3021 [========>.....................] - ETA: 0s - loss: 0.0746 - mse: 0.0746
2600/3021 [========================>.....] - ETA: 0s - loss: 0.0611 - mse: 0.0611
3021/3021 [==============================] - 1s 180us/sample - loss: 0.0597 - mse: 0.0597 - val_loss: 0.0803 - val_mse: 0.0803
Epoch 18/50
100/3021 [..............................] - ETA: 0s - loss: 0.0587 - mse: 0.0587
1500/3021 [=============>................] - ETA: 0s - loss: 0.0519 - mse: 0.0519
3000/3021 [============================>.] - ETA: 0s - loss: 0.0519 - mse: 0.0519
3021/3021 [==============================] - 1s 174us/sample - loss: 0.0522 - mse: 0.0522 - val_loss: 0.0549 - val_mse: 0.0549
Epoch 19/50
100/3021 [..............................] - ETA: 0s - loss: 0.0428 - mse: 0.0428
1100/3021 [=========>....................] - ETA: 0s - loss: 0.0650 - mse: 0.0650
2700/3021 [=========================>....] - ETA: 0s - loss: 0.0652 - mse: 0.0652
3021/3021 [==============================] - 1s 172us/sample - loss: 0.0647 - mse: 0.0647 - val_loss: 0.0704 - val_mse: 0.0704
Epoch 20/50
100/3021 [..............................] - ETA: 0s - loss: 0.0562 - mse: 0.0562
1400/3021 [============>.................] - ETA: 0s - loss: 0.0724 - mse: 0.0724
2900/3021 [===========================>..] - ETA: 0s - loss: 0.0618 - mse: 0.0618
3021/3021 [==============================] - 1s 169us/sample - loss: 0.0609 - mse: 0.0609 - val_loss: 0.0563 - val_mse: 0.0563
Epoch 21/50
100/3021 [..............................] - ETA: 0s - loss: 0.0387 - mse: 0.0387
1100/3021 [=========>....................] - ETA: 0s - loss: 0.0564 - mse: 0.0564
2700/3021 [=========================>....] - ETA: 0s - loss: 0.0509 - mse: 0.0509
3021/3021 [==============================] - 1s 174us/sample - loss: 0.0496 - mse: 0.0496 - val_loss: 0.0550 - val_mse: 0.0550
Epoch 22/50
100/3021 [..............................] - ETA: 0s - loss: 0.0458 - mse: 0.0458
1500/3021 [=============>................] - ETA: 0s - loss: 0.0425 - mse: 0.0425
3021/3021 [==============================] - 1s 166us/sample - loss: 0.0460 - mse: 0.0460 - val_loss: 0.0579 - val_mse: 0.0579
Epoch 23/50
100/3021 [..............................] - ETA: 0s - loss: 0.0281 - mse: 0.0281
1600/3021 [==============>...............] - ETA: 0s - loss: 0.0448 - mse: 0.0448
3000/3021 [============================>.] - ETA: 0s - loss: 0.0407 - mse: 0.0407
3021/3021 [==============================] - 1s 182us/sample - loss: 0.0407 - mse: 0.0407 - val_loss: 0.0603 - val_mse: 0.0603
Epoch 24/50
100/3021 [..............................] - ETA: 0s - loss: 0.0454 - mse: 0.0454
1400/3021 [============>.................] - ETA: 0s - loss: 0.0373 - mse: 0.0373
2900/3021 [===========================>..] - ETA: 0s - loss: 0.0393 - mse: 0.0393
3021/3021 [==============================] - 1s 176us/sample - loss: 0.0391 - mse: 0.0391 - val_loss: 0.0561 - val_mse: 0.0561
Epoch 25/50
100/3021 [..............................] - ETA: 0s - loss: 0.0385 - mse: 0.0385
1600/3021 [==============>...............] - ETA: 0s - loss: 0.0447 - mse: 0.0447
3000/3021 [============================>.] - ETA: 0s - loss: 0.0434 - mse: 0.0434
3021/3021 [==============================] - 1s 167us/sample - loss: 0.0435 - mse: 0.0435 - val_loss: 0.0560 - val_mse: 0.0560
Epoch 26/50
100/3021 [..............................] - ETA: 0s - loss: 0.0367 - mse: 0.0367
1600/3021 [==============>...............] - ETA: 0s - loss: 0.0500 - mse: 0.0500
3021/3021 [==============================] - 0s 164us/sample - loss: 0.0539 - mse: 0.0539 - val_loss: 0.0565 - val_mse: 0.0565
Epoch 27/50
100/3021 [..............................] - ETA: 0s - loss: 0.0508 - mse: 0.0508
1500/3021 [=============>................] - ETA: 0s - loss: 0.0465 - mse: 0.0465
3021/3021 [==============================] - 0s 163us/sample - loss: 0.0463 - mse: 0.0463 - val_loss: 0.0767 - val_mse: 0.0767
Epoch 28/50
100/3021 [..............................] - ETA: 0s - loss: 0.0586 - mse: 0.0586
1400/3021 [============>.................] - ETA: 0s - loss: 0.0668 - mse: 0.0668
2800/3021 [==========================>...] - ETA: 0s - loss: 0.0580 - mse: 0.0580
3021/3021 [==============================] - 1s 172us/sample - loss: 0.0562 - mse: 0.0562 - val_loss: 0.0538 - val_mse: 0.0538
Epoch 29/50
100/3021 [..............................] - ETA: 0s - loss: 0.0339 - mse: 0.0339
1200/3021 [==========>...................] - ETA: 0s - loss: 0.0396 - mse: 0.0396
2700/3021 [=========================>....] - ETA: 0s - loss: 0.0382 - mse: 0.0382
3021/3021 [==============================] - 1s 171us/sample - loss: 0.0389 - mse: 0.0389 - val_loss: 0.0435 - val_mse: 0.0435
Epoch 30/50
100/3021 [..............................] - ETA: 0s - loss: 0.0332 - mse: 0.0332
1600/3021 [==============>...............] - ETA: 0s - loss: 0.0442 - mse: 0.0442
3000/3021 [============================>.] - ETA: 0s - loss: 0.0431 - mse: 0.0431
3021/3021 [==============================] - 1s 176us/sample - loss: 0.0429 - mse: 0.0429 - val_loss: 0.0805 - val_mse: 0.0805
Epoch 31/50
100/3021 [..............................] - ETA: 0s - loss: 0.0628 - mse: 0.0628
1200/3021 [==========>...................] - ETA: 0s - loss: 0.0618 - mse: 0.0618
2900/3021 [===========================>..] - ETA: 0s - loss: 0.0503 - mse: 0.0503
3021/3021 [==============================] - 1s 167us/sample - loss: 0.0498 - mse: 0.0498 - val_loss: 0.0555 - val_mse: 0.0555
Epoch 32/50
100/3021 [..............................] - ETA: 0s - loss: 0.0549 - mse: 0.0549
1700/3021 [===============>..............] - ETA: 0s - loss: 0.0436 - mse: 0.0436
3021/3021 [==============================] - 1s 168us/sample - loss: 0.0441 - mse: 0.0441 - val_loss: 0.0555 - val_mse: 0.0555
Epoch 33/50
100/3021 [..............................] - ETA: 0s - loss: 0.0407 - mse: 0.0407
1100/3021 [=========>....................] - ETA: 0s - loss: 0.0410 - mse: 0.0410
2700/3021 [=========================>....] - ETA: 0s - loss: 0.0381 - mse: 0.0381
3021/3021 [==============================] - 1s 167us/sample - loss: 0.0386 - mse: 0.0386 - val_loss: 0.0597 - val_mse: 0.0597
Epoch 34/50
100/3021 [..............................] - ETA: 0s - loss: 0.0464 - mse: 0.0464
1600/3021 [==============>...............] - ETA: 0s - loss: 0.0454 - mse: 0.0454
3021/3021 [==============================] - 1s 166us/sample - loss: 0.0438 - mse: 0.0438 - val_loss: 0.0499 - val_mse: 0.0499
Epoch 35/50
100/3021 [..............................] - ETA: 0s - loss: 0.0435 - mse: 0.0435
1100/3021 [=========>....................] - ETA: 0s - loss: 0.0482 - mse: 0.0482
2800/3021 [==========================>...] - ETA: 0s - loss: 0.0431 - mse: 0.0431
3021/3021 [==============================] - 1s 172us/sample - loss: 0.0432 - mse: 0.0432 - val_loss: 0.0521 - val_mse: 0.0521
Epoch 36/50
100/3021 [..............................] - ETA: 0s - loss: 0.0351 - mse: 0.0351
1600/3021 [==============>...............] - ETA: 0s - loss: 0.0427 - mse: 0.0427
3021/3021 [==============================] - 1s 183us/sample - loss: 0.0400 - mse: 0.0400 - val_loss: 0.0510 - val_mse: 0.0510
Epoch 37/50
100/3021 [..............................] - ETA: 0s - loss: 0.0513 - mse: 0.0513
1500/3021 [=============>................] - ETA: 0s - loss: 0.0405 - mse: 0.0405
3021/3021 [==============================] - 1s 177us/sample - loss: 0.0366 - mse: 0.0366 - val_loss: 0.0966 - val_mse: 0.0966
Epoch 38/50
100/3021 [..............................] - ETA: 0s - loss: 0.0913 - mse: 0.0913
1600/3021 [==============>...............] - ETA: 0s - loss: 0.0839 - mse: 0.0839
3000/3021 [============================>.] - ETA: 0s - loss: 0.0741 - mse: 0.0741
3021/3021 [==============================] - 1s 169us/sample - loss: 0.0742 - mse: 0.0742 - val_loss: 0.0912 - val_mse: 0.0912
Epoch 39/50
100/3021 [..............................] - ETA: 0s - loss: 0.0697 - mse: 0.0697
1700/3021 [===============>..............] - ETA: 0s - loss: 0.0816 - mse: 0.0816
3021/3021 [==============================] - 1s 173us/sample - loss: 0.0691 - mse: 0.0691 - val_loss: 0.1035 - val_mse: 0.1035
Epoch 40/50
100/3021 [..............................] - ETA: 0s - loss: 0.0985 - mse: 0.0985
1700/3021 [===============>..............] - ETA: 0s - loss: 0.0913 - mse: 0.0913
3021/3021 [==============================] - 1s 184us/sample - loss: 0.0879 - mse: 0.0879 - val_loss: 0.0826 - val_mse: 0.0826
Epoch 41/50
100/3021 [..............................] - ETA: 0s - loss: 0.0848 - mse: 0.0848
1600/3021 [==============>...............] - ETA: 0s - loss: 0.0496 - mse: 0.0496
3021/3021 [==============================] - 0s 162us/sample - loss: 0.0452 - mse: 0.0452 - val_loss: 0.0422 - val_mse: 0.0422
Epoch 42/50
100/3021 [..............................] - ETA: 0s - loss: 0.0368 - mse: 0.0368
1600/3021 [==============>...............] - ETA: 0s - loss: 0.0492 - mse: 0.0492
2900/3021 [===========================>..] - ETA: 0s - loss: 0.0460 - mse: 0.0460
3021/3021 [==============================] - 1s 168us/sample - loss: 0.0458 - mse: 0.0458 - val_loss: 0.0511 - val_mse: 0.0511
Epoch 43/50
100/3021 [..............................] - ETA: 0s - loss: 0.0319 - mse: 0.0319
1300/3021 [===========>..................] - ETA: 0s - loss: 0.0417 - mse: 0.0417
2800/3021 [==========================>...] - ETA: 0s - loss: 0.0405 - mse: 0.0405
3021/3021 [==============================] - 1s 179us/sample - loss: 0.0405 - mse: 0.0405 - val_loss: 0.0471 - val_mse: 0.0471
Epoch 44/50
100/3021 [..............................] - ETA: 0s - loss: 0.0455 - mse: 0.0455
1100/3021 [=========>....................] - ETA: 0s - loss: 0.0389 - mse: 0.0389
2700/3021 [=========================>....] - ETA: 0s - loss: 0.0337 - mse: 0.0337
3021/3021 [==============================] - 1s 173us/sample - loss: 0.0329 - mse: 0.0329 - val_loss: 0.0457 - val_mse: 0.0457
Epoch 45/50
100/3021 [..............................] - ETA: 0s - loss: 0.0463 - mse: 0.0463
1500/3021 [=============>................] - ETA: 0s - loss: 0.0321 - mse: 0.0321
3000/3021 [============================>.] - ETA: 0s - loss: 0.0311 - mse: 0.0311
3021/3021 [==============================] - 1s 170us/sample - loss: 0.0312 - mse: 0.0312 - val_loss: 0.0424 - val_mse: 0.0424
Epoch 46/50
100/3021 [..............................] - ETA: 0s - loss: 0.0264 - mse: 0.0264
1200/3021 [==========>...................] - ETA: 0s - loss: 0.0336 - mse: 0.0336
2900/3021 [===========================>..] - ETA: 0s - loss: 0.0314 - mse: 0.0314
3021/3021 [==============================] - 1s 175us/sample - loss: 0.0314 - mse: 0.0314 - val_loss: 0.0513 - val_mse: 0.0513
Epoch 47/50
100/3021 [..............................] - ETA: 0s - loss: 0.0407 - mse: 0.0407
1700/3021 [===============>..............] - ETA: 0s - loss: 0.0295 - mse: 0.0295
3021/3021 [==============================] - 1s 169us/sample - loss: 0.0302 - mse: 0.0302 - val_loss: 0.0431 - val_mse: 0.0431
Epoch 48/50
100/3021 [..............................] - ETA: 0s - loss: 0.0297 - mse: 0.0297
1100/3021 [=========>....................] - ETA: 0s - loss: 0.0343 - mse: 0.0343
2800/3021 [==========================>...] - ETA: 0s - loss: 0.0357 - mse: 0.0357
3021/3021 [==============================] - 1s 166us/sample - loss: 0.0367 - mse: 0.0367 - val_loss: 0.0629 - val_mse: 0.0629
Epoch 49/50
100/3021 [..............................] - ETA: 0s - loss: 0.0459 - mse: 0.0459
1600/3021 [==============>...............] - ETA: 0s - loss: 0.0528 - mse: 0.0528
3021/3021 [==============================] - 1s 174us/sample - loss: 0.0465 - mse: 0.0465 - val_loss: 0.0574 - val_mse: 0.0574
Epoch 50/50
100/3021 [..............................] - ETA: 0s - loss: 0.0458 - mse: 0.0458
1500/3021 [=============>................] - ETA: 0s - loss: 0.0383 - mse: 0.0383
2900/3021 [===========================>..] - ETA: 0s - loss: 0.0353 - mse: 0.0353
3021/3021 [==============================] - 1s 183us/sample - loss: 0.0353 - mse: 0.0353 - val_loss: 0.0531 - val_mse: 0.0531Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-05-04T00-57-48Z
Training run 12/46 (flags = list(392, 392, 1e-04, 100, 30, "sigmoid", "tanh", 0.2, 0.2))
Using run directory runs/2020-05-04T00-58-18Z
> FLAGS <- flags(
+ flag_numeric("nodes1", 128),
+ flag_numeric("nodes2", 128),
+ flag_numeric("batch_size", 100),
+ flag_string("activation1" .... [TRUNCATED]
> model = keras_model_sequential()
> model %>%
+ layer_dense(units=FLAGS$nodes1, activation=FLAGS$activation1, input_shape=dim(efw_train2)[2]) %>%
+ layer_dropout(FLAGS$dropout1) %> .... [TRUNCATED]
> model %>% compile(
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ loss = 'mse',
+ metrics = c('mse')
+ )
> model %>% fit(
+ as.matrix(efw_train2), train2Label,
+ epochs=FLAGS$epochs,
+ batch_size=FLAGS$batch_size,
+ validation_data=list(as.matrix( .... [TRUNCATED]
Train on 3021 samples, validate on 334 samples
Epoch 1/30
100/3021 [..............................] - ETA: 7s - loss: 54.6100 - mse: 54.6100
1600/3021 [==============>...............] - ETA: 0s - loss: 49.3755 - mse: 49.3755
3000/3021 [============================>.] - ETA: 0s - loss: 47.5178 - mse: 47.5178
3021/3021 [==============================] - 1s 268us/sample - loss: 47.4419 - mse: 47.4419 - val_loss: 42.6848 - val_mse: 42.6848
Epoch 2/30
100/3021 [..............................] - ETA: 0s - loss: 42.6243 - mse: 42.6243
1600/3021 [==============>...............] - ETA: 0s - loss: 40.4353 - mse: 40.4353
3021/3021 [==============================] - 1s 173us/sample - loss: 38.7555 - mse: 38.7555 - val_loss: 34.8945 - val_mse: 34.8945
Epoch 3/30
100/3021 [..............................] - ETA: 0s - loss: 34.5911 - mse: 34.5911
1400/3021 [============>.................] - ETA: 0s - loss: 33.6267 - mse: 33.6267
2900/3021 [===========================>..] - ETA: 0s - loss: 31.5991 - mse: 31.5991
3021/3021 [==============================] - 1s 174us/sample - loss: 31.4935 - mse: 31.4935 - val_loss: 28.2237 - val_mse: 28.2237
Epoch 4/30
100/3021 [..............................] - ETA: 0s - loss: 28.7777 - mse: 28.7777
1600/3021 [==============>...............] - ETA: 0s - loss: 26.6193 - mse: 26.6193
3000/3021 [============================>.] - ETA: 0s - loss: 25.4069 - mse: 25.4069
3021/3021 [==============================] - 1s 167us/sample - loss: 25.3872 - mse: 25.3872 - val_loss: 22.5988 - val_mse: 22.5988
Epoch 5/30
100/3021 [..............................] - ETA: 0s - loss: 22.3913 - mse: 22.3913
1400/3021 [============>.................] - ETA: 0s - loss: 21.2566 - mse: 21.2566
2600/3021 [========================>.....] - ETA: 0s - loss: 20.3807 - mse: 20.3807
3021/3021 [==============================] - 1s 180us/sample - loss: 20.0724 - mse: 20.0724 - val_loss: 17.9010 - val_mse: 17.9010
Epoch 6/30
100/3021 [..............................] - ETA: 0s - loss: 17.5377 - mse: 17.5377
1000/3021 [========>.....................] - ETA: 0s - loss: 17.1351 - mse: 17.1351
2400/3021 [======================>.......] - ETA: 0s - loss: 16.1733 - mse: 16.1733
3021/3021 [==============================] - 1s 171us/sample - loss: 15.7877 - mse: 15.7877 - val_loss: 14.0161 - val_mse: 14.0161
Epoch 7/30
100/3021 [..............................] - ETA: 0s - loss: 13.9323 - mse: 13.9323
1500/3021 [=============>................] - ETA: 0s - loss: 12.9959 - mse: 12.9959
2900/3021 [===========================>..] - ETA: 0s - loss: 12.3426 - mse: 12.3426
3021/3021 [==============================] - 1s 175us/sample - loss: 12.2770 - mse: 12.2771 - val_loss: 10.8514 - val_mse: 10.8514
Epoch 8/30
100/3021 [..............................] - ETA: 0s - loss: 10.1617 - mse: 10.1617
1100/3021 [=========>....................] - ETA: 0s - loss: 10.3843 - mse: 10.3843
2700/3021 [=========================>....] - ETA: 0s - loss: 9.6976 - mse: 9.6976
3021/3021 [==============================] - 1s 171us/sample - loss: 9.5356 - mse: 9.5356 - val_loss: 8.2873 - val_mse: 8.2873
Epoch 9/30
100/3021 [..............................] - ETA: 0s - loss: 7.9587 - mse: 7.9587
1200/3021 [==========>...................] - ETA: 0s - loss: 7.7267 - mse: 7.7267
2400/3021 [======================>.......] - ETA: 0s - loss: 7.4227 - mse: 7.4227
3021/3021 [==============================] - 1s 238us/sample - loss: 7.2329 - mse: 7.2329 - val_loss: 6.2499 - val_mse: 6.2499
Epoch 10/30
100/3021 [..............................] - ETA: 0s - loss: 5.8618 - mse: 5.8618
1200/3021 [==========>...................] - ETA: 0s - loss: 5.9315 - mse: 5.9315
2400/3021 [======================>.......] - ETA: 0s - loss: 5.5875 - mse: 5.5875
3021/3021 [==============================] - 1s 230us/sample - loss: 5.4276 - mse: 5.4276 - val_loss: 4.6457 - val_mse: 4.6457
Epoch 11/30
100/3021 [..............................] - ETA: 0s - loss: 4.8505 - mse: 4.8505
1200/3021 [==========>...................] - ETA: 0s - loss: 4.3137 - mse: 4.3137
2400/3021 [======================>.......] - ETA: 0s - loss: 4.0855 - mse: 4.0855
3021/3021 [==============================] - 1s 214us/sample - loss: 3.9476 - mse: 3.9476 - val_loss: 3.4213 - val_mse: 3.4213
Epoch 12/30
100/3021 [..............................] - ETA: 0s - loss: 3.2550 - mse: 3.2550
1100/3021 [=========>....................] - ETA: 0s - loss: 3.2319 - mse: 3.2319
2600/3021 [========================>.....] - ETA: 0s - loss: 3.0329 - mse: 3.0329
3021/3021 [==============================] - 1s 172us/sample - loss: 2.9708 - mse: 2.9708 - val_loss: 2.4848 - val_mse: 2.4848
Epoch 13/30
100/3021 [..............................] - ETA: 0s - loss: 2.5109 - mse: 2.5109
1500/3021 [=============>................] - ETA: 0s - loss: 2.3235 - mse: 2.3235
3000/3021 [============================>.] - ETA: 0s - loss: 2.1610 - mse: 2.1610
3021/3021 [==============================] - 1s 172us/sample - loss: 2.1565 - mse: 2.1565 - val_loss: 1.7851 - val_mse: 1.7851
Epoch 14/30
100/3021 [..............................] - ETA: 0s - loss: 1.9734 - mse: 1.9734
1600/3021 [==============>...............] - ETA: 0s - loss: 1.6612 - mse: 1.6612
3021/3021 [==============================] - 1s 168us/sample - loss: 1.5583 - mse: 1.5583 - val_loss: 1.2764 - val_mse: 1.2764
Epoch 15/30
100/3021 [..............................] - ETA: 0s - loss: 1.2503 - mse: 1.2503
1100/3021 [=========>....................] - ETA: 0s - loss: 1.2445 - mse: 1.2445
2500/3021 [=======================>......] - ETA: 0s - loss: 1.1670 - mse: 1.1670
3021/3021 [==============================] - 1s 183us/sample - loss: 1.1357 - mse: 1.1357 - val_loss: 0.9084 - val_mse: 0.9084
Epoch 16/30
100/3021 [..............................] - ETA: 0s - loss: 1.0305 - mse: 1.0305
1100/3021 [=========>....................] - ETA: 0s - loss: 0.9302 - mse: 0.9302
2600/3021 [========================>.....] - ETA: 0s - loss: 0.8634 - mse: 0.8634
3021/3021 [==============================] - 1s 171us/sample - loss: 0.8481 - mse: 0.8481 - val_loss: 0.6462 - val_mse: 0.6462
Epoch 17/30
100/3021 [..............................] - ETA: 0s - loss: 0.7447 - mse: 0.7447
1400/3021 [============>.................] - ETA: 0s - loss: 0.6795 - mse: 0.6795
3000/3021 [============================>.] - ETA: 0s - loss: 0.6355 - mse: 0.6355
3021/3021 [==============================] - 1s 172us/sample - loss: 0.6345 - mse: 0.6345 - val_loss: 0.4623 - val_mse: 0.4623
Epoch 18/30
100/3021 [..............................] - ETA: 0s - loss: 0.5414 - mse: 0.5414
1100/3021 [=========>....................] - ETA: 0s - loss: 0.5354 - mse: 0.5354
2800/3021 [==========================>...] - ETA: 0s - loss: 0.5014 - mse: 0.5014
3021/3021 [==============================] - 1s 171us/sample - loss: 0.4966 - mse: 0.4966 - val_loss: 0.3334 - val_mse: 0.3334
Epoch 19/30
100/3021 [..............................] - ETA: 0s - loss: 0.3163 - mse: 0.3163
1600/3021 [==============>...............] - ETA: 0s - loss: 0.4239 - mse: 0.4239
3021/3021 [==============================] - 1s 167us/sample - loss: 0.4045 - mse: 0.4045 - val_loss: 0.2458 - val_mse: 0.2458
Epoch 20/30
100/3021 [..............................] - ETA: 0s - loss: 0.3742 - mse: 0.3742
1200/3021 [==========>...................] - ETA: 0s - loss: 0.3540 - mse: 0.3540
2900/3021 [===========================>..] - ETA: 0s - loss: 0.3275 - mse: 0.3275
3021/3021 [==============================] - 1s 169us/sample - loss: 0.3256 - mse: 0.3256 - val_loss: 0.1875 - val_mse: 0.1875
Epoch 21/30
100/3021 [..............................] - ETA: 0s - loss: 0.2293 - mse: 0.2293
1100/3021 [=========>....................] - ETA: 0s - loss: 0.3113 - mse: 0.3113
2700/3021 [=========================>....] - ETA: 0s - loss: 0.3035 - mse: 0.3035
3021/3021 [==============================] - 1s 173us/sample - loss: 0.2974 - mse: 0.2974 - val_loss: 0.1491 - val_mse: 0.1491
Epoch 22/30
100/3021 [..............................] - ETA: 0s - loss: 0.3056 - mse: 0.3056
1600/3021 [==============>...............] - ETA: 0s - loss: 0.2639 - mse: 0.2639
3021/3021 [==============================] - 0s 164us/sample - loss: 0.2672 - mse: 0.2672 - val_loss: 0.1244 - val_mse: 0.1244
Epoch 23/30
100/3021 [..............................] - ETA: 0s - loss: 0.2120 - mse: 0.2120
1700/3021 [===============>..............] - ETA: 0s - loss: 0.2475 - mse: 0.2475
3021/3021 [==============================] - 0s 165us/sample - loss: 0.2428 - mse: 0.2428 - val_loss: 0.1069 - val_mse: 0.1069
Epoch 24/30
100/3021 [..............................] - ETA: 0s - loss: 0.1762 - mse: 0.1762
1700/3021 [===============>..............] - ETA: 0s - loss: 0.2561 - mse: 0.2561
3021/3021 [==============================] - 0s 163us/sample - loss: 0.2375 - mse: 0.2375 - val_loss: 0.0950 - val_mse: 0.0950
Epoch 25/30
100/3021 [..............................] - ETA: 0s - loss: 0.2840 - mse: 0.2840
1600/3021 [==============>...............] - ETA: 0s - loss: 0.2398 - mse: 0.2398
3000/3021 [============================>.] - ETA: 0s - loss: 0.2365 - mse: 0.2365
3021/3021 [==============================] - 1s 172us/sample - loss: 0.2367 - mse: 0.2367 - val_loss: 0.0874 - val_mse: 0.0874
Epoch 26/30
100/3021 [..............................] - ETA: 0s - loss: 0.1872 - mse: 0.1872
1500/3021 [=============>................] - ETA: 0s - loss: 0.2071 - mse: 0.2071
2900/3021 [===========================>..] - ETA: 0s - loss: 0.2214 - mse: 0.2214
3021/3021 [==============================] - 1s 169us/sample - loss: 0.2208 - mse: 0.2208 - val_loss: 0.0826 - val_mse: 0.0826
Epoch 27/30
100/3021 [..............................] - ETA: 0s - loss: 0.1766 - mse: 0.1766
1500/3021 [=============>................] - ETA: 0s - loss: 0.2043 - mse: 0.2043
3000/3021 [============================>.] - ETA: 0s - loss: 0.2099 - mse: 0.2099
3021/3021 [==============================] - 1s 169us/sample - loss: 0.2108 - mse: 0.2108 - val_loss: 0.0793 - val_mse: 0.0793
Epoch 28/30
100/3021 [..............................] - ETA: 0s - loss: 0.2090 - mse: 0.2090
1700/3021 [===============>..............] - ETA: 0s - loss: 0.2181 - mse: 0.2181
3000/3021 [============================>.] - ETA: 0s - loss: 0.2159 - mse: 0.2159
3021/3021 [==============================] - 1s 171us/sample - loss: 0.2154 - mse: 0.2154 - val_loss: 0.0768 - val_mse: 0.0768
Epoch 29/30
100/3021 [..............................] - ETA: 0s - loss: 0.1689 - mse: 0.1689
1300/3021 [===========>..................] - ETA: 0s - loss: 0.2060 - mse: 0.2060
2900/3021 [===========================>..] - ETA: 0s - loss: 0.2057 - mse: 0.2057
3021/3021 [==============================] - 1s 170us/sample - loss: 0.2066 - mse: 0.2066 - val_loss: 0.0749 - val_mse: 0.0749
Epoch 30/30
100/3021 [..............................] - ETA: 0s - loss: 0.1801 - mse: 0.1801
1400/3021 [============>.................] - ETA: 0s - loss: 0.2137 - mse: 0.2137
2900/3021 [===========================>..] - ETA: 0s - loss: 0.2122 - mse: 0.2122
3021/3021 [==============================] - 1s 171us/sample - loss: 0.2123 - mse: 0.2123 - val_loss: 0.0737 - val_mse: 0.0737Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-05-04T00-58-18Z
Training run 13/46 (flags = list(64, 128, 0.001, 500, 30, "relu", "sigmoid", 0.05, 0.1))
Using run directory runs/2020-05-04T00-58-38Z
> FLAGS <- flags(
+ flag_numeric("nodes1", 128),
+ flag_numeric("nodes2", 128),
+ flag_numeric("batch_size", 100),
+ flag_string("activation1" .... [TRUNCATED]
> model = keras_model_sequential()
> model %>%
+ layer_dense(units=FLAGS$nodes1, activation=FLAGS$activation1, input_shape=dim(efw_train2)[2]) %>%
+ layer_dropout(FLAGS$dropout1) %> .... [TRUNCATED]
> model %>% compile(
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ loss = 'mse',
+ metrics = c('mse')
+ )
> model %>% fit(
+ as.matrix(efw_train2), train2Label,
+ epochs=FLAGS$epochs,
+ batch_size=FLAGS$batch_size,
+ validation_data=list(as.matrix( .... [TRUNCATED]
Train on 3021 samples, validate on 334 samples
Epoch 1/30
500/3021 [===>..........................] - ETA: 1s - loss: 39.2717 - mse: 39.2717
3021/3021 [==============================] - 1s 233us/sample - loss: 37.0934 - mse: 37.0934 - val_loss: 34.0211 - val_mse: 34.0211
Epoch 2/30
500/3021 [===>..........................] - ETA: 0s - loss: 34.1473 - mse: 34.1473
3021/3021 [==============================] - 0s 141us/sample - loss: 32.1278 - mse: 32.1278 - val_loss: 29.3691 - val_mse: 29.3691
Epoch 3/30
500/3021 [===>..........................] - ETA: 0s - loss: 28.7505 - mse: 28.7505
3021/3021 [==============================] - 0s 160us/sample - loss: 27.4538 - mse: 27.4538 - val_loss: 24.9983 - val_mse: 24.9983
Epoch 4/30
500/3021 [===>..........................] - ETA: 0s - loss: 24.2239 - mse: 24.2239
3021/3021 [==============================] - 0s 138us/sample - loss: 23.2207 - mse: 23.2207 - val_loss: 21.0689 - val_mse: 21.0689
Epoch 5/30
500/3021 [===>..........................] - ETA: 0s - loss: 20.3545 - mse: 20.3545
3021/3021 [==============================] - 0s 131us/sample - loss: 19.5056 - mse: 19.5056 - val_loss: 17.6981 - val_mse: 17.6981
Epoch 6/30
500/3021 [===>..........................] - ETA: 0s - loss: 16.8917 - mse: 16.8917
3021/3021 [==============================] - 0s 139us/sample - loss: 16.3444 - mse: 16.3444 - val_loss: 14.9738 - val_mse: 14.9738
Epoch 7/30
500/3021 [===>..........................] - ETA: 0s - loss: 14.9281 - mse: 14.9281
3021/3021 [==============================] - 0s 130us/sample - loss: 13.8622 - mse: 13.8622 - val_loss: 12.8494 - val_mse: 12.8494
Epoch 8/30
500/3021 [===>..........................] - ETA: 0s - loss: 12.1577 - mse: 12.1577
3021/3021 [==============================] - 0s 129us/sample - loss: 12.0088 - mse: 12.0088 - val_loss: 11.2020 - val_mse: 11.2020
Epoch 9/30
500/3021 [===>..........................] - ETA: 0s - loss: 10.6123 - mse: 10.6123
3021/3021 [==============================] - 0s 132us/sample - loss: 10.5106 - mse: 10.5105 - val_loss: 9.8566 - val_mse: 9.8566
Epoch 10/30
500/3021 [===>..........................] - ETA: 0s - loss: 9.6405 - mse: 9.6405
3021/3021 [==============================] - 0s 136us/sample - loss: 9.2906 - mse: 9.2906 - val_loss: 8.7366 - val_mse: 8.7366
Epoch 11/30
500/3021 [===>..........................] - ETA: 0s - loss: 8.3268 - mse: 8.3268
3021/3021 [==============================] - 0s 127us/sample - loss: 8.2462 - mse: 8.2462 - val_loss: 7.7855 - val_mse: 7.7855
Epoch 12/30
500/3021 [===>..........................] - ETA: 0s - loss: 7.8508 - mse: 7.8508
3021/3021 [==============================] - 0s 128us/sample - loss: 7.3752 - mse: 7.3752 - val_loss: 6.9567 - val_mse: 6.9567
Epoch 13/30
500/3021 [===>..........................] - ETA: 0s - loss: 7.3152 - mse: 7.3152
3021/3021 [==============================] - 0s 139us/sample - loss: 6.6228 - mse: 6.6228 - val_loss: 6.2240 - val_mse: 6.2240
Epoch 14/30
500/3021 [===>..........................] - ETA: 0s - loss: 6.0135 - mse: 6.0135
3021/3021 [==============================] - 0s 140us/sample - loss: 5.9538 - mse: 5.9538 - val_loss: 5.5859 - val_mse: 5.5859
Epoch 15/30
500/3021 [===>..........................] - ETA: 0s - loss: 5.1359 - mse: 5.1359
3021/3021 [==============================] - 0s 138us/sample - loss: 5.3756 - mse: 5.3756 - val_loss: 5.0218 - val_mse: 5.0218
Epoch 16/30
500/3021 [===>..........................] - ETA: 0s - loss: 5.3032 - mse: 5.3032
3021/3021 [==============================] - 0s 126us/sample - loss: 4.7893 - mse: 4.7893 - val_loss: 4.5072 - val_mse: 4.5072
Epoch 17/30
500/3021 [===>..........................] - ETA: 0s - loss: 4.8810 - mse: 4.8810
3021/3021 [==============================] - 0s 131us/sample - loss: 4.3383 - mse: 4.3383 - val_loss: 4.0378 - val_mse: 4.0378
Epoch 18/30
500/3021 [===>..........................] - ETA: 0s - loss: 4.1431 - mse: 4.1431
3021/3021 [==============================] - 0s 136us/sample - loss: 3.8555 - mse: 3.8555 - val_loss: 3.6122 - val_mse: 3.6122
Epoch 19/30
500/3021 [===>..........................] - ETA: 0s - loss: 3.5701 - mse: 3.5701
3021/3021 [==============================] - 0s 135us/sample - loss: 3.4417 - mse: 3.4417 - val_loss: 3.2322 - val_mse: 3.2322
Epoch 20/30
500/3021 [===>..........................] - ETA: 0s - loss: 3.1786 - mse: 3.1786
3021/3021 [==============================] - 0s 126us/sample - loss: 3.0667 - mse: 3.0667 - val_loss: 2.8802 - val_mse: 2.8802
Epoch 21/30
500/3021 [===>..........................] - ETA: 0s - loss: 2.9845 - mse: 2.9845
3021/3021 [==============================] - 0s 133us/sample - loss: 2.7101 - mse: 2.7101 - val_loss: 2.5619 - val_mse: 2.5619
Epoch 22/30
500/3021 [===>..........................] - ETA: 0s - loss: 2.7802 - mse: 2.7802
3021/3021 [==============================] - 0s 130us/sample - loss: 2.4318 - mse: 2.4318 - val_loss: 2.2845 - val_mse: 2.2845
Epoch 23/30
500/3021 [===>..........................] - ETA: 0s - loss: 2.4541 - mse: 2.4541
3021/3021 [==============================] - 0s 138us/sample - loss: 2.1780 - mse: 2.1780 - val_loss: 2.0458 - val_mse: 2.0458
Epoch 24/30
500/3021 [===>..........................] - ETA: 0s - loss: 1.9134 - mse: 1.9134
3021/3021 [==============================] - 0s 135us/sample - loss: 1.9306 - mse: 1.9306 - val_loss: 1.8324 - val_mse: 1.8324
Epoch 25/30
500/3021 [===>..........................] - ETA: 0s - loss: 1.6663 - mse: 1.6663
3021/3021 [==============================] - 0s 132us/sample - loss: 1.7466 - mse: 1.7466 - val_loss: 1.6419 - val_mse: 1.6419
Epoch 26/30
500/3021 [===>..........................] - ETA: 0s - loss: 1.6745 - mse: 1.6745
3021/3021 [==============================] - 0s 128us/sample - loss: 1.5741 - mse: 1.5741 - val_loss: 1.4742 - val_mse: 1.4742
Epoch 27/30
500/3021 [===>..........................] - ETA: 0s - loss: 1.5708 - mse: 1.5708
3021/3021 [==============================] - 0s 131us/sample - loss: 1.4041 - mse: 1.4041 - val_loss: 1.3304 - val_mse: 1.3304
Epoch 28/30
500/3021 [===>..........................] - ETA: 0s - loss: 1.2314 - mse: 1.2314
3021/3021 [==============================] - 0s 136us/sample - loss: 1.2804 - mse: 1.2804 - val_loss: 1.2069 - val_mse: 1.2069
Epoch 29/30
500/3021 [===>..........................] - ETA: 0s - loss: 1.2718 - mse: 1.2718
3021/3021 [==============================] - 0s 138us/sample - loss: 1.1671 - mse: 1.1671 - val_loss: 1.1045 - val_mse: 1.1045
Epoch 30/30
500/3021 [===>..........................] - ETA: 0s - loss: 1.1702 - mse: 1.1702
3021/3021 [==============================] - 0s 132us/sample - loss: 1.0805 - mse: 1.0805 - val_loss: 1.0150 - val_mse: 1.0150Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-05-04T00-58-38Z
Training run 14/46 (flags = list(128, 392, 1e-04, 200, 50, "tanh", "tanh", 0.2, 0.1))
Using run directory runs/2020-05-04T00-58-53Z
> FLAGS <- flags(
+ flag_numeric("nodes1", 128),
+ flag_numeric("nodes2", 128),
+ flag_numeric("batch_size", 100),
+ flag_string("activation1" .... [TRUNCATED]
> model = keras_model_sequential()
> model %>%
+ layer_dense(units=FLAGS$nodes1, activation=FLAGS$activation1, input_shape=dim(efw_train2)[2]) %>%
+ layer_dropout(FLAGS$dropout1) %> .... [TRUNCATED]
> model %>% compile(
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ loss = 'mse',
+ metrics = c('mse')
+ )
> model %>% fit(
+ as.matrix(efw_train2), train2Label,
+ epochs=FLAGS$epochs,
+ batch_size=FLAGS$batch_size,
+ validation_data=list(as.matrix( .... [TRUNCATED]
Train on 3021 samples, validate on 334 samples
Epoch 1/50
200/3021 [>.............................] - ETA: 3s - loss: 43.0197 - mse: 43.0197
3021/3021 [==============================] - 1s 235us/sample - loss: 42.8982 - mse: 42.8982 - val_loss: 42.7453 - val_mse: 42.7453
Epoch 2/50
200/3021 [>.............................] - ETA: 0s - loss: 42.2829 - mse: 42.2829
3021/3021 [==============================] - 0s 147us/sample - loss: 42.0513 - mse: 42.0513 - val_loss: 42.0012 - val_mse: 42.0012
Epoch 3/50
200/3021 [>.............................] - ETA: 0s - loss: 40.5125 - mse: 40.5125
3021/3021 [==============================] - 0s 140us/sample - loss: 41.2570 - mse: 41.2570 - val_loss: 41.3043 - val_mse: 41.3043
Epoch 4/50
200/3021 [>.............................] - ETA: 0s - loss: 41.3006 - mse: 41.3006
3021/3021 [==============================] - 0s 139us/sample - loss: 40.5701 - mse: 40.5701 - val_loss: 40.6312 - val_mse: 40.6312
Epoch 5/50
200/3021 [>.............................] - ETA: 0s - loss: 40.1138 - mse: 40.1138
3021/3021 [==============================] - 0s 148us/sample - loss: 39.8702 - mse: 39.8702 - val_loss: 39.9592 - val_mse: 39.9592
Epoch 6/50
200/3021 [>.............................] - ETA: 0s - loss: 38.8827 - mse: 38.8827
2200/3021 [====================>.........] - ETA: 0s - loss: 39.2185 - mse: 39.2185
3021/3021 [==============================] - 0s 156us/sample - loss: 39.1132 - mse: 39.1132 - val_loss: 39.2994 - val_mse: 39.2994
Epoch 7/50
200/3021 [>.............................] - ETA: 0s - loss: 38.3492 - mse: 38.3492
3021/3021 [==============================] - 0s 143us/sample - loss: 38.4957 - mse: 38.4957 - val_loss: 38.6230 - val_mse: 38.6230
Epoch 8/50
200/3021 [>.............................] - ETA: 0s - loss: 38.3486 - mse: 38.3486
3021/3021 [==============================] - 0s 137us/sample - loss: 37.8340 - mse: 37.8340 - val_loss: 37.9013 - val_mse: 37.9013
Epoch 9/50
200/3021 [>.............................] - ETA: 0s - loss: 37.7070 - mse: 37.7070
3021/3021 [==============================] - 0s 146us/sample - loss: 37.1735 - mse: 37.1735 - val_loss: 37.2218 - val_mse: 37.2218
Epoch 10/50
200/3021 [>.............................] - ETA: 0s - loss: 36.1727 - mse: 36.1727
3021/3021 [==============================] - 0s 141us/sample - loss: 36.3605 - mse: 36.3605 - val_loss: 36.5319 - val_mse: 36.5319
Epoch 11/50
200/3021 [>.............................] - ETA: 0s - loss: 36.1696 - mse: 36.1696
2400/3021 [======================>.......] - ETA: 0s - loss: 35.7566 - mse: 35.7566
3021/3021 [==============================] - 0s 147us/sample - loss: 35.7561 - mse: 35.7561 - val_loss: 35.7993 - val_mse: 35.7993
Epoch 12/50
200/3021 [>.............................] - ETA: 0s - loss: 35.4758 - mse: 35.4758
3021/3021 [==============================] - 0s 152us/sample - loss: 35.0113 - mse: 35.0113 - val_loss: 35.0903 - val_mse: 35.0903
Epoch 13/50
200/3021 [>.............................] - ETA: 0s - loss: 34.9057 - mse: 34.9057
3021/3021 [==============================] - 0s 141us/sample - loss: 34.3086 - mse: 34.3086 - val_loss: 34.3700 - val_mse: 34.3700
Epoch 14/50
200/3021 [>.............................] - ETA: 0s - loss: 33.7916 - mse: 33.7916
2800/3021 [==========================>...] - ETA: 0s - loss: 33.5616 - mse: 33.5616
3021/3021 [==============================] - 0s 148us/sample - loss: 33.5168 - mse: 33.5168 - val_loss: 33.6404 - val_mse: 33.6404
Epoch 15/50
200/3021 [>.............................] - ETA: 0s - loss: 32.8114 - mse: 32.8114
3021/3021 [==============================] - 0s 142us/sample - loss: 32.8626 - mse: 32.8626 - val_loss: 32.9127 - val_mse: 32.9127
Epoch 16/50
200/3021 [>.............................] - ETA: 0s - loss: 32.1306 - mse: 32.1306
3021/3021 [==============================] - 0s 140us/sample - loss: 32.0381 - mse: 32.0381 - val_loss: 32.1365 - val_mse: 32.1365
Epoch 17/50
200/3021 [>.............................] - ETA: 0s - loss: 31.8570 - mse: 31.8570
3021/3021 [==============================] - 0s 141us/sample - loss: 31.3547 - mse: 31.3547 - val_loss: 31.3411 - val_mse: 31.3411
Epoch 18/50
200/3021 [>.............................] - ETA: 0s - loss: 30.6967 - mse: 30.6967
3021/3021 [==============================] - 0s 137us/sample - loss: 30.4299 - mse: 30.4299 - val_loss: 30.5551 - val_mse: 30.5551
Epoch 19/50
200/3021 [>.............................] - ETA: 0s - loss: 30.3443 - mse: 30.3443
3021/3021 [==============================] - 0s 140us/sample - loss: 29.6056 - mse: 29.6056 - val_loss: 29.7593 - val_mse: 29.7593
Epoch 20/50
200/3021 [>.............................] - ETA: 0s - loss: 29.1563 - mse: 29.1563
3021/3021 [==============================] - 0s 137us/sample - loss: 28.8432 - mse: 28.8432 - val_loss: 28.9688 - val_mse: 28.9688
Epoch 21/50
200/3021 [>.............................] - ETA: 0s - loss: 28.6613 - mse: 28.6613
3021/3021 [==============================] - 0s 134us/sample - loss: 28.0460 - mse: 28.0460 - val_loss: 28.1854 - val_mse: 28.1854
Epoch 22/50
200/3021 [>.............................] - ETA: 0s - loss: 27.3279 - mse: 27.3279
3021/3021 [==============================] - 0s 142us/sample - loss: 27.1663 - mse: 27.1663 - val_loss: 27.3710 - val_mse: 27.3710
Epoch 23/50
200/3021 [>.............................] - ETA: 0s - loss: 26.6001 - mse: 26.6001
3021/3021 [==============================] - 0s 139us/sample - loss: 26.3983 - mse: 26.3983 - val_loss: 26.5643 - val_mse: 26.5643
Epoch 24/50
200/3021 [>.............................] - ETA: 0s - loss: 25.9854 - mse: 25.9854
3021/3021 [==============================] - 0s 139us/sample - loss: 25.4556 - mse: 25.4556 - val_loss: 25.7267 - val_mse: 25.7267
Epoch 25/50
200/3021 [>.............................] - ETA: 0s - loss: 25.5957 - mse: 25.5957
3021/3021 [==============================] - 0s 157us/sample - loss: 24.7304 - mse: 24.7304 - val_loss: 24.8474 - val_mse: 24.8474
Epoch 26/50
200/3021 [>.............................] - ETA: 0s - loss: 24.1386 - mse: 24.1386
3021/3021 [==============================] - 0s 145us/sample - loss: 23.8606 - mse: 23.8606 - val_loss: 23.9802 - val_mse: 23.9802
Epoch 27/50
200/3021 [>.............................] - ETA: 0s - loss: 23.6451 - mse: 23.6451
2400/3021 [======================>.......] - ETA: 0s - loss: 23.1634 - mse: 23.1634
3021/3021 [==============================] - 0s 153us/sample - loss: 23.0090 - mse: 23.0090 - val_loss: 23.1220 - val_mse: 23.1220
Epoch 28/50
200/3021 [>.............................] - ETA: 0s - loss: 22.8828 - mse: 22.8828
3021/3021 [==============================] - 0s 145us/sample - loss: 22.1482 - mse: 22.1482 - val_loss: 22.3025 - val_mse: 22.3025
Epoch 29/50
200/3021 [>.............................] - ETA: 0s - loss: 22.2061 - mse: 22.2061
3021/3021 [==============================] - 0s 134us/sample - loss: 21.3724 - mse: 21.3724 - val_loss: 21.4675 - val_mse: 21.4675
Epoch 30/50
200/3021 [>.............................] - ETA: 0s - loss: 21.1164 - mse: 21.1164
2200/3021 [====================>.........] - ETA: 0s - loss: 20.5120 - mse: 20.5120
3021/3021 [==============================] - 0s 147us/sample - loss: 20.4702 - mse: 20.4702 - val_loss: 20.6516 - val_mse: 20.6516
Epoch 31/50
200/3021 [>.............................] - ETA: 0s - loss: 20.6569 - mse: 20.6569
3021/3021 [==============================] - 0s 142us/sample - loss: 19.6972 - mse: 19.6972 - val_loss: 19.8200 - val_mse: 19.8200
Epoch 32/50
200/3021 [>.............................] - ETA: 0s - loss: 19.3768 - mse: 19.3768
2200/3021 [====================>.........] - ETA: 0s - loss: 18.8549 - mse: 18.8549
3021/3021 [==============================] - 0s 147us/sample - loss: 18.7976 - mse: 18.7976 - val_loss: 19.0034 - val_mse: 19.0034
Epoch 33/50
200/3021 [>.............................] - ETA: 0s - loss: 18.3342 - mse: 18.3342
3021/3021 [==============================] - 0s 149us/sample - loss: 18.0476 - mse: 18.0476 - val_loss: 18.1921 - val_mse: 18.1920
Epoch 34/50
200/3021 [>.............................] - ETA: 0s - loss: 17.3566 - mse: 17.3566
3021/3021 [==============================] - 0s 136us/sample - loss: 17.2541 - mse: 17.2541 - val_loss: 17.3794 - val_mse: 17.3794
Epoch 35/50
200/3021 [>.............................] - ETA: 0s - loss: 16.4925 - mse: 16.4925
3021/3021 [==============================] - 0s 138us/sample - loss: 16.4111 - mse: 16.4111 - val_loss: 16.5560 - val_mse: 16.5560
Epoch 36/50
200/3021 [>.............................] - ETA: 0s - loss: 15.8449 - mse: 15.8449
3021/3021 [==============================] - 0s 141us/sample - loss: 15.6260 - mse: 15.6260 - val_loss: 15.7528 - val_mse: 15.7528
Epoch 37/50
200/3021 [>.............................] - ETA: 0s - loss: 15.0471 - mse: 15.0471
3021/3021 [==============================] - 0s 138us/sample - loss: 14.8467 - mse: 14.8467 - val_loss: 14.9848 - val_mse: 14.9848
Epoch 38/50
200/3021 [>.............................] - ETA: 0s - loss: 14.5779 - mse: 14.5779
3021/3021 [==============================] - 0s 147us/sample - loss: 14.1651 - mse: 14.1651 - val_loss: 14.2436 - val_mse: 14.2436
Epoch 39/50
200/3021 [>.............................] - ETA: 0s - loss: 13.7512 - mse: 13.7512
3021/3021 [==============================] - 0s 134us/sample - loss: 13.3876 - mse: 13.3876 - val_loss: 13.5066 - val_mse: 13.5066
Epoch 40/50
200/3021 [>.............................] - ETA: 0s - loss: 13.0065 - mse: 13.0065
3021/3021 [==============================] - 0s 142us/sample - loss: 12.6773 - mse: 12.6773 - val_loss: 12.7586 - val_mse: 12.7586
Epoch 41/50
200/3021 [>.............................] - ETA: 0s - loss: 12.3085 - mse: 12.3085
2600/3021 [========================>.....] - ETA: 0s - loss: 11.9716 - mse: 11.9716
3021/3021 [==============================] - 0s 150us/sample - loss: 11.9512 - mse: 11.9512 - val_loss: 12.0705 - val_mse: 12.0705
Epoch 42/50
200/3021 [>.............................] - ETA: 0s - loss: 11.9933 - mse: 11.9933
2800/3021 [==========================>...] - ETA: 0s - loss: 11.3300 - mse: 11.3300
3021/3021 [==============================] - 0s 149us/sample - loss: 11.2871 - mse: 11.2871 - val_loss: 11.3841 - val_mse: 11.3841
Epoch 43/50
200/3021 [>.............................] - ETA: 0s - loss: 11.3572 - mse: 11.3572
3021/3021 [==============================] - 0s 134us/sample - loss: 10.6742 - mse: 10.6742 - val_loss: 10.7273 - val_mse: 10.7273
Epoch 44/50
200/3021 [>.............................] - ETA: 0s - loss: 10.0715 - mse: 10.0715
3021/3021 [==============================] - 0s 137us/sample - loss: 10.0443 - mse: 10.0443 - val_loss: 10.1069 - val_mse: 10.1069
Epoch 45/50
200/3021 [>.............................] - ETA: 0s - loss: 9.9787 - mse: 9.9787
3021/3021 [==============================] - 0s 141us/sample - loss: 9.3388 - mse: 9.3388 - val_loss: 9.4962 - val_mse: 9.4962
Epoch 46/50
200/3021 [>.............................] - ETA: 0s - loss: 8.9947 - mse: 8.9947
2600/3021 [========================>.....] - ETA: 0s - loss: 8.8953 - mse: 8.8953
3021/3021 [==============================] - 0s 142us/sample - loss: 8.8177 - mse: 8.8177 - val_loss: 8.9197 - val_mse: 8.9197
Epoch 47/50
200/3021 [>.............................] - ETA: 0s - loss: 8.6041 - mse: 8.6041
3021/3021 [==============================] - 0s 138us/sample - loss: 8.2937 - mse: 8.2937 - val_loss: 8.3336 - val_mse: 8.3336
Epoch 48/50
200/3021 [>.............................] - ETA: 0s - loss: 7.6236 - mse: 7.6236
3021/3021 [==============================] - 0s 133us/sample - loss: 7.6285 - mse: 7.6285 - val_loss: 7.7731 - val_mse: 7.7731
Epoch 49/50
200/3021 [>.............................] - ETA: 0s - loss: 7.3107 - mse: 7.3107
3021/3021 [==============================] - 0s 151us/sample - loss: 7.1900 - mse: 7.1900 - val_loss: 7.2573 - val_mse: 7.2573
Epoch 50/50
200/3021 [>.............................] - ETA: 0s - loss: 6.8458 - mse: 6.8458
2200/3021 [====================>.........] - ETA: 0s - loss: 6.7199 - mse: 6.7199
3021/3021 [==============================] - 0s 150us/sample - loss: 6.6276 - mse: 6.6276 - val_loss: 6.7482 - val_mse: 6.7482Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-05-04T00-58-53Z
Training run 15/46 (flags = list(128, 128, 0.01, 200, 50, "sigmoid", "tanh", 0.1, 0.05))
Using run directory runs/2020-05-04T00-59-19Z
> FLAGS <- flags(
+ flag_numeric("nodes1", 128),
+ flag_numeric("nodes2", 128),
+ flag_numeric("batch_size", 100),
+ flag_string("activation1" .... [TRUNCATED]
> model = keras_model_sequential()
> model %>%
+ layer_dense(units=FLAGS$nodes1, activation=FLAGS$activation1, input_shape=dim(efw_train2)[2]) %>%
+ layer_dropout(FLAGS$dropout1) %> .... [TRUNCATED]
> model %>% compile(
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ loss = 'mse',
+ metrics = c('mse')
+ )
> model %>% fit(
+ as.matrix(efw_train2), train2Label,
+ epochs=FLAGS$epochs,
+ batch_size=FLAGS$batch_size,
+ validation_data=list(as.matrix( .... [TRUNCATED]
Train on 3021 samples, validate on 334 samples
Epoch 1/50
200/3021 [>.............................] - ETA: 3s - loss: 41.5439 - mse: 41.5439
3021/3021 [==============================] - 1s 251us/sample - loss: 10.4736 - mse: 10.4736 - val_loss: 3.6912 - val_mse: 3.6912
Epoch 2/50
200/3021 [>.............................] - ETA: 0s - loss: 4.1924 - mse: 4.1924
3021/3021 [==============================] - 0s 144us/sample - loss: 1.8058 - mse: 1.8058 - val_loss: 0.5794 - val_mse: 0.5794
Epoch 3/50
200/3021 [>.............................] - ETA: 0s - loss: 0.5530 - mse: 0.5530
3021/3021 [==============================] - 0s 151us/sample - loss: 0.4982 - mse: 0.4982 - val_loss: 0.1238 - val_mse: 0.1238
Epoch 4/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2132 - mse: 0.2132
3021/3021 [==============================] - 0s 143us/sample - loss: 0.2084 - mse: 0.2084 - val_loss: 0.0674 - val_mse: 0.0674
Epoch 5/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1143 - mse: 0.1143
3000/3021 [============================>.] - ETA: 0s - loss: 0.1533 - mse: 0.1533
3021/3021 [==============================] - 0s 164us/sample - loss: 0.1531 - mse: 0.1531 - val_loss: 0.0558 - val_mse: 0.0558
Epoch 6/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1169 - mse: 0.1169
2400/3021 [======================>.......] - ETA: 0s - loss: 0.1294 - mse: 0.1294
3021/3021 [==============================] - 0s 144us/sample - loss: 0.1322 - mse: 0.1322 - val_loss: 0.0457 - val_mse: 0.0457
Epoch 7/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1305 - mse: 0.1305
3021/3021 [==============================] - 0s 147us/sample - loss: 0.1287 - mse: 0.1287 - val_loss: 0.0412 - val_mse: 0.0412
Epoch 8/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1119 - mse: 0.1119
3021/3021 [==============================] - 0s 146us/sample - loss: 0.1213 - mse: 0.1213 - val_loss: 0.0426 - val_mse: 0.0426
Epoch 9/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1374 - mse: 0.1374
3021/3021 [==============================] - 0s 145us/sample - loss: 0.1232 - mse: 0.1232 - val_loss: 0.0388 - val_mse: 0.0388
Epoch 10/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1132 - mse: 0.1132
3021/3021 [==============================] - 0s 140us/sample - loss: 0.1201 - mse: 0.1201 - val_loss: 0.0411 - val_mse: 0.0411
Epoch 11/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1185 - mse: 0.1185
2800/3021 [==========================>...] - ETA: 0s - loss: 0.1211 - mse: 0.1211
3021/3021 [==============================] - 0s 151us/sample - loss: 0.1206 - mse: 0.1206 - val_loss: 0.0388 - val_mse: 0.0388
Epoch 12/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1344 - mse: 0.1344
3021/3021 [==============================] - 0s 147us/sample - loss: 0.1164 - mse: 0.1164 - val_loss: 0.0377 - val_mse: 0.0377
Epoch 13/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1050 - mse: 0.1050
3021/3021 [==============================] - 0s 146us/sample - loss: 0.1139 - mse: 0.1139 - val_loss: 0.0361 - val_mse: 0.0361
Epoch 14/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1160 - mse: 0.1160
3021/3021 [==============================] - 0s 147us/sample - loss: 0.1188 - mse: 0.1188 - val_loss: 0.0388 - val_mse: 0.0388
Epoch 15/50
200/3021 [>.............................] - ETA: 0s - loss: 0.0923 - mse: 0.0923
3021/3021 [==============================] - 0s 142us/sample - loss: 0.1193 - mse: 0.1193 - val_loss: 0.0430 - val_mse: 0.0430
Epoch 16/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1235 - mse: 0.1235
2400/3021 [======================>.......] - ETA: 0s - loss: 0.1172 - mse: 0.1172
3021/3021 [==============================] - 0s 151us/sample - loss: 0.1173 - mse: 0.1173 - val_loss: 0.0419 - val_mse: 0.0419
Epoch 17/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1129 - mse: 0.1129
3021/3021 [==============================] - 0s 141us/sample - loss: 0.1203 - mse: 0.1203 - val_loss: 0.0360 - val_mse: 0.0360
Epoch 18/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1052 - mse: 0.1052
3021/3021 [==============================] - 0s 140us/sample - loss: 0.1099 - mse: 0.1099 - val_loss: 0.0378 - val_mse: 0.0378
Epoch 19/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1239 - mse: 0.1239
3021/3021 [==============================] - 0s 144us/sample - loss: 0.1115 - mse: 0.1115 - val_loss: 0.0368 - val_mse: 0.0368
Epoch 20/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1397 - mse: 0.1397
2200/3021 [====================>.........] - ETA: 0s - loss: 0.1191 - mse: 0.1191
3021/3021 [==============================] - 0s 151us/sample - loss: 0.1158 - mse: 0.1158 - val_loss: 0.0436 - val_mse: 0.0436
Epoch 21/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1192 - mse: 0.1192
3021/3021 [==============================] - 0s 136us/sample - loss: 0.1085 - mse: 0.1085 - val_loss: 0.0387 - val_mse: 0.0387
Epoch 22/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1200 - mse: 0.1200
3021/3021 [==============================] - 0s 142us/sample - loss: 0.1103 - mse: 0.1103 - val_loss: 0.0366 - val_mse: 0.0366
Epoch 23/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1074 - mse: 0.1074
3021/3021 [==============================] - 0s 144us/sample - loss: 0.1087 - mse: 0.1087 - val_loss: 0.0355 - val_mse: 0.0355
Epoch 24/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1008 - mse: 0.1008
3021/3021 [==============================] - 0s 139us/sample - loss: 0.1087 - mse: 0.1087 - val_loss: 0.0392 - val_mse: 0.0392
Epoch 25/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1064 - mse: 0.1064
2400/3021 [======================>.......] - ETA: 0s - loss: 0.1041 - mse: 0.1041
3021/3021 [==============================] - 0s 143us/sample - loss: 0.1022 - mse: 0.1022 - val_loss: 0.0383 - val_mse: 0.0383
Epoch 26/50
200/3021 [>.............................] - ETA: 0s - loss: 0.0962 - mse: 0.0962
3021/3021 [==============================] - 0s 144us/sample - loss: 0.1060 - mse: 0.1060 - val_loss: 0.0406 - val_mse: 0.0406
Epoch 27/50
200/3021 [>.............................] - ETA: 0s - loss: 0.0813 - mse: 0.0813
3000/3021 [============================>.] - ETA: 0s - loss: 0.1069 - mse: 0.1069
3021/3021 [==============================] - 0s 147us/sample - loss: 0.1068 - mse: 0.1068 - val_loss: 0.0370 - val_mse: 0.0370
Epoch 28/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1135 - mse: 0.1135
3021/3021 [==============================] - 0s 140us/sample - loss: 0.1050 - mse: 0.1050 - val_loss: 0.0376 - val_mse: 0.0376
Epoch 29/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1155 - mse: 0.1155
3021/3021 [==============================] - 0s 134us/sample - loss: 0.0970 - mse: 0.0970 - val_loss: 0.0460 - val_mse: 0.0460
Epoch 30/50
200/3021 [>.............................] - ETA: 0s - loss: 0.0979 - mse: 0.0979
3021/3021 [==============================] - 0s 147us/sample - loss: 0.1018 - mse: 0.1018 - val_loss: 0.0475 - val_mse: 0.0475
Epoch 31/50
200/3021 [>.............................] - ETA: 0s - loss: 0.0893 - mse: 0.0893
3021/3021 [==============================] - 0s 142us/sample - loss: 0.0990 - mse: 0.0990 - val_loss: 0.0410 - val_mse: 0.0410
Epoch 32/50
200/3021 [>.............................] - ETA: 0s - loss: 0.0781 - mse: 0.0781
2800/3021 [==========================>...] - ETA: 0s - loss: 0.0973 - mse: 0.0973
3021/3021 [==============================] - 0s 149us/sample - loss: 0.0980 - mse: 0.0980 - val_loss: 0.0496 - val_mse: 0.0496
Epoch 33/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1094 - mse: 0.1094
3021/3021 [==============================] - 0s 141us/sample - loss: 0.1027 - mse: 0.1027 - val_loss: 0.0377 - val_mse: 0.0377
Epoch 34/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1069 - mse: 0.1069
3021/3021 [==============================] - 0s 136us/sample - loss: 0.0894 - mse: 0.0894 - val_loss: 0.0339 - val_mse: 0.0339
Epoch 35/50
200/3021 [>.............................] - ETA: 0s - loss: 0.0727 - mse: 0.0727
3021/3021 [==============================] - 0s 141us/sample - loss: 0.0925 - mse: 0.0925 - val_loss: 0.0333 - val_mse: 0.0333
Epoch 36/50
200/3021 [>.............................] - ETA: 0s - loss: 0.0807 - mse: 0.0807
3021/3021 [==============================] - 0s 142us/sample - loss: 0.0908 - mse: 0.0908 - val_loss: 0.0431 - val_mse: 0.0431
Epoch 37/50
200/3021 [>.............................] - ETA: 0s - loss: 0.0973 - mse: 0.0973
3021/3021 [==============================] - 0s 139us/sample - loss: 0.0937 - mse: 0.0937 - val_loss: 0.0349 - val_mse: 0.0349
Epoch 38/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1003 - mse: 0.1003
3021/3021 [==============================] - 0s 137us/sample - loss: 0.0924 - mse: 0.0924 - val_loss: 0.0370 - val_mse: 0.0370
Epoch 39/50
200/3021 [>.............................] - ETA: 0s - loss: 0.0824 - mse: 0.0824
3021/3021 [==============================] - 0s 131us/sample - loss: 0.0899 - mse: 0.0899 - val_loss: 0.0374 - val_mse: 0.0374
Epoch 40/50
200/3021 [>.............................] - ETA: 0s - loss: 0.0758 - mse: 0.0758
3021/3021 [==============================] - 0s 150us/sample - loss: 0.0872 - mse: 0.0872 - val_loss: 0.0404 - val_mse: 0.0404
Epoch 41/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1043 - mse: 0.1043
3021/3021 [==============================] - 0s 142us/sample - loss: 0.0865 - mse: 0.0865 - val_loss: 0.0396 - val_mse: 0.0396
Epoch 42/50
200/3021 [>.............................] - ETA: 0s - loss: 0.0752 - mse: 0.0752
3021/3021 [==============================] - 0s 139us/sample - loss: 0.0878 - mse: 0.0878 - val_loss: 0.0395 - val_mse: 0.0395
Epoch 43/50
200/3021 [>.............................] - ETA: 0s - loss: 0.0843 - mse: 0.0843
3021/3021 [==============================] - 0s 137us/sample - loss: 0.0877 - mse: 0.0877 - val_loss: 0.0367 - val_mse: 0.0367
Epoch 44/50
200/3021 [>.............................] - ETA: 0s - loss: 0.0628 - mse: 0.0628
3021/3021 [==============================] - 0s 144us/sample - loss: 0.0825 - mse: 0.0825 - val_loss: 0.0338 - val_mse: 0.0338
Epoch 45/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1049 - mse: 0.1049
3021/3021 [==============================] - 0s 148us/sample - loss: 0.0837 - mse: 0.0837 - val_loss: 0.0370 - val_mse: 0.0370
Epoch 46/50
200/3021 [>.............................] - ETA: 0s - loss: 0.0488 - mse: 0.0488
2200/3021 [====================>.........] - ETA: 0s - loss: 0.0798 - mse: 0.0798
3021/3021 [==============================] - 0s 146us/sample - loss: 0.0807 - mse: 0.0807 - val_loss: 0.0375 - val_mse: 0.0375
Epoch 47/50
200/3021 [>.............................] - ETA: 0s - loss: 0.0750 - mse: 0.0750
3021/3021 [==============================] - 0s 136us/sample - loss: 0.0770 - mse: 0.0770 - val_loss: 0.0350 - val_mse: 0.0350
Epoch 48/50
200/3021 [>.............................] - ETA: 0s - loss: 0.0722 - mse: 0.0722
3021/3021 [==============================] - 0s 135us/sample - loss: 0.0757 - mse: 0.0757 - val_loss: 0.0357 - val_mse: 0.0357
Epoch 49/50
200/3021 [>.............................] - ETA: 0s - loss: 0.0858 - mse: 0.0858
3021/3021 [==============================] - 0s 146us/sample - loss: 0.0760 - mse: 0.0760 - val_loss: 0.0337 - val_mse: 0.0337
Epoch 50/50
200/3021 [>.............................] - ETA: 0s - loss: 0.0737 - mse: 0.0737
2200/3021 [====================>.........] - ETA: 0s - loss: 0.0766 - mse: 0.0766
3021/3021 [==============================] - 0s 146us/sample - loss: 0.0755 - mse: 0.0755 - val_loss: 0.0379 - val_mse: 0.0379Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-05-04T00-59-19Z
Training run 16/46 (flags = list(64, 64, 0.01, 500, 100, "sigmoid", "sigmoid", 0.5, 0.1))
Using run directory runs/2020-05-04T00-59-44Z
> FLAGS <- flags(
+ flag_numeric("nodes1", 128),
+ flag_numeric("nodes2", 128),
+ flag_numeric("batch_size", 100),
+ flag_string("activation1" .... [TRUNCATED]
> model = keras_model_sequential()
> model %>%
+ layer_dense(units=FLAGS$nodes1, activation=FLAGS$activation1, input_shape=dim(efw_train2)[2]) %>%
+ layer_dropout(FLAGS$dropout1) %> .... [TRUNCATED]
> model %>% compile(
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ loss = 'mse',
+ metrics = c('mse')
+ )
> model %>% fit(
+ as.matrix(efw_train2), train2Label,
+ epochs=FLAGS$epochs,
+ batch_size=FLAGS$batch_size,
+ validation_data=list(as.matrix( .... [TRUNCATED]
Train on 3021 samples, validate on 334 samples
Epoch 1/100
500/3021 [===>..........................] - ETA: 1s - loss: 39.0599 - mse: 39.0599
3021/3021 [==============================] - 1s 239us/sample - loss: 27.0610 - mse: 27.0610 - val_loss: 11.6162 - val_mse: 11.6162
Epoch 2/100
500/3021 [===>..........................] - ETA: 0s - loss: 12.0526 - mse: 12.0526
3021/3021 [==============================] - 0s 143us/sample - loss: 7.3136 - mse: 7.3136 - val_loss: 1.1319 - val_mse: 1.1319
Epoch 3/100
500/3021 [===>..........................] - ETA: 0s - loss: 2.1753 - mse: 2.1753
3021/3021 [==============================] - 0s 141us/sample - loss: 1.8533 - mse: 1.8533 - val_loss: 0.5039 - val_mse: 0.5039
Epoch 4/100
500/3021 [===>..........................] - ETA: 0s - loss: 2.1307 - mse: 2.1307
3021/3021 [==============================] - 0s 137us/sample - loss: 2.4912 - mse: 2.4912 - val_loss: 0.9294 - val_mse: 0.9294
Epoch 5/100
500/3021 [===>..........................] - ETA: 0s - loss: 2.6698 - mse: 2.6698
3021/3021 [==============================] - 0s 139us/sample - loss: 2.1927 - mse: 2.1927 - val_loss: 0.2555 - val_mse: 0.2555
Epoch 6/100
500/3021 [===>..........................] - ETA: 0s - loss: 1.5788 - mse: 1.5788
3021/3021 [==============================] - 0s 131us/sample - loss: 1.4751 - mse: 1.4751 - val_loss: 0.1517 - val_mse: 0.1517
Epoch 7/100
500/3021 [===>..........................] - ETA: 0s - loss: 1.3805 - mse: 1.3805
3021/3021 [==============================] - 0s 161us/sample - loss: 1.4468 - mse: 1.4468 - val_loss: 0.3085 - val_mse: 0.3085
Epoch 8/100
500/3021 [===>..........................] - ETA: 0s - loss: 1.4189 - mse: 1.4189
3021/3021 [==============================] - 0s 160us/sample - loss: 1.4479 - mse: 1.4479 - val_loss: 0.2479 - val_mse: 0.2479
Epoch 9/100
500/3021 [===>..........................] - ETA: 0s - loss: 1.3543 - mse: 1.3543
3021/3021 [==============================] - 0s 151us/sample - loss: 1.3639 - mse: 1.3639 - val_loss: 0.1187 - val_mse: 0.1187
Epoch 10/100
500/3021 [===>..........................] - ETA: 0s - loss: 1.3507 - mse: 1.3507
3021/3021 [==============================] - 0s 156us/sample - loss: 1.2471 - mse: 1.2471 - val_loss: 0.0853 - val_mse: 0.0853
Epoch 11/100
500/3021 [===>..........................] - ETA: 0s - loss: 1.1278 - mse: 1.1278
3021/3021 [==============================] - 0s 144us/sample - loss: 1.2308 - mse: 1.2308 - val_loss: 0.0763 - val_mse: 0.0763
Epoch 12/100
500/3021 [===>..........................] - ETA: 0s - loss: 1.1260 - mse: 1.1260
3021/3021 [==============================] - 0s 152us/sample - loss: 1.2394 - mse: 1.2394 - val_loss: 0.0767 - val_mse: 0.0767
Epoch 13/100
500/3021 [===>..........................] - ETA: 0s - loss: 1.0789 - mse: 1.0789
3021/3021 [==============================] - 0s 136us/sample - loss: 1.1619 - mse: 1.1619 - val_loss: 0.0773 - val_mse: 0.0773
Epoch 14/100
500/3021 [===>..........................] - ETA: 0s - loss: 1.2131 - mse: 1.2131
3021/3021 [==============================] - 0s 135us/sample - loss: 1.1533 - mse: 1.1533 - val_loss: 0.0759 - val_mse: 0.0759
Epoch 15/100
500/3021 [===>..........................] - ETA: 0s - loss: 1.1639 - mse: 1.1639
3021/3021 [==============================] - 0s 130us/sample - loss: 1.1184 - mse: 1.1184 - val_loss: 0.0836 - val_mse: 0.0836
Epoch 16/100
500/3021 [===>..........................] - ETA: 0s - loss: 1.0858 - mse: 1.0858
3021/3021 [==============================] - 0s 135us/sample - loss: 1.1241 - mse: 1.1241 - val_loss: 0.0966 - val_mse: 0.0966
Epoch 17/100
500/3021 [===>..........................] - ETA: 0s - loss: 1.0185 - mse: 1.0185
3021/3021 [==============================] - 0s 131us/sample - loss: 1.0382 - mse: 1.0382 - val_loss: 0.1057 - val_mse: 0.1057
Epoch 18/100
500/3021 [===>..........................] - ETA: 0s - loss: 1.0543 - mse: 1.0543
3021/3021 [==============================] - 0s 131us/sample - loss: 1.0991 - mse: 1.0991 - val_loss: 0.0744 - val_mse: 0.0744
Epoch 19/100
500/3021 [===>..........................] - ETA: 0s - loss: 1.2922 - mse: 1.2922
3021/3021 [==============================] - 0s 140us/sample - loss: 1.0865 - mse: 1.0865 - val_loss: 0.0648 - val_mse: 0.0648
Epoch 20/100
500/3021 [===>..........................] - ETA: 0s - loss: 1.0322 - mse: 1.0322
3021/3021 [==============================] - 0s 143us/sample - loss: 1.0487 - mse: 1.0487 - val_loss: 0.0678 - val_mse: 0.0678
Epoch 21/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.9875 - mse: 0.9875
3021/3021 [==============================] - 0s 140us/sample - loss: 0.9988 - mse: 0.9988 - val_loss: 0.1048 - val_mse: 0.1048
Epoch 22/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.9910 - mse: 0.9910
3021/3021 [==============================] - 0s 165us/sample - loss: 1.0126 - mse: 1.0126 - val_loss: 0.0952 - val_mse: 0.0952
Epoch 23/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.8832 - mse: 0.8832
3021/3021 [==============================] - 0s 139us/sample - loss: 0.9491 - mse: 0.9491 - val_loss: 0.0815 - val_mse: 0.0815
Epoch 24/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.9728 - mse: 0.9728
3021/3021 [==============================] - 0s 140us/sample - loss: 0.9931 - mse: 0.9931 - val_loss: 0.0903 - val_mse: 0.0903
Epoch 25/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.9576 - mse: 0.9576
3021/3021 [==============================] - 0s 137us/sample - loss: 0.9727 - mse: 0.9727 - val_loss: 0.0779 - val_mse: 0.0779
Epoch 26/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.7738 - mse: 0.7738
3021/3021 [==============================] - 0s 136us/sample - loss: 0.9392 - mse: 0.9392 - val_loss: 0.0781 - val_mse: 0.0781
Epoch 27/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.9228 - mse: 0.9228
3021/3021 [==============================] - 0s 131us/sample - loss: 0.9179 - mse: 0.9179 - val_loss: 0.0772 - val_mse: 0.0772
Epoch 28/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.8592 - mse: 0.8592
3021/3021 [==============================] - 0s 144us/sample - loss: 0.9236 - mse: 0.9236 - val_loss: 0.0813 - val_mse: 0.0813
Epoch 29/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.8792 - mse: 0.8792
3021/3021 [==============================] - 1s 186us/sample - loss: 0.9372 - mse: 0.9372 - val_loss: 0.1028 - val_mse: 0.1028
Epoch 30/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.8360 - mse: 0.8360
3021/3021 [==============================] - 0s 157us/sample - loss: 0.8707 - mse: 0.8707 - val_loss: 0.0899 - val_mse: 0.0899
Epoch 31/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.8700 - mse: 0.8700
3021/3021 [==============================] - 0s 152us/sample - loss: 0.8352 - mse: 0.8352 - val_loss: 0.0855 - val_mse: 0.0855
Epoch 32/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.9462 - mse: 0.9462
3021/3021 [==============================] - 0s 137us/sample - loss: 0.8845 - mse: 0.8845 - val_loss: 0.0761 - val_mse: 0.0761
Epoch 33/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.8184 - mse: 0.8184
3021/3021 [==============================] - 0s 143us/sample - loss: 0.8385 - mse: 0.8385 - val_loss: 0.0835 - val_mse: 0.0835
Epoch 34/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.8050 - mse: 0.8050
3021/3021 [==============================] - 0s 138us/sample - loss: 0.8303 - mse: 0.8303 - val_loss: 0.0901 - val_mse: 0.0901
Epoch 35/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.7592 - mse: 0.7592
3021/3021 [==============================] - 0s 142us/sample - loss: 0.7950 - mse: 0.7950 - val_loss: 0.0842 - val_mse: 0.0842
Epoch 36/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.8498 - mse: 0.8498
3021/3021 [==============================] - 0s 129us/sample - loss: 0.8066 - mse: 0.8066 - val_loss: 0.0717 - val_mse: 0.0717
Epoch 37/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.7032 - mse: 0.7032
3021/3021 [==============================] - 0s 135us/sample - loss: 0.8142 - mse: 0.8142 - val_loss: 0.0656 - val_mse: 0.0656
Epoch 38/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.6984 - mse: 0.6984
3021/3021 [==============================] - 0s 149us/sample - loss: 0.7668 - mse: 0.7668 - val_loss: 0.0818 - val_mse: 0.0818
Epoch 39/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.6659 - mse: 0.6659
3021/3021 [==============================] - 0s 134us/sample - loss: 0.7586 - mse: 0.7586 - val_loss: 0.0876 - val_mse: 0.0876
Epoch 40/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.7994 - mse: 0.7994
3021/3021 [==============================] - 0s 131us/sample - loss: 0.7674 - mse: 0.7674 - val_loss: 0.0757 - val_mse: 0.0757
Epoch 41/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.7989 - mse: 0.7989
3021/3021 [==============================] - 0s 134us/sample - loss: 0.7652 - mse: 0.7652 - val_loss: 0.0779 - val_mse: 0.0779
Epoch 42/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.7040 - mse: 0.7040
3021/3021 [==============================] - 0s 139us/sample - loss: 0.7579 - mse: 0.7579 - val_loss: 0.0955 - val_mse: 0.0955
Epoch 43/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.7913 - mse: 0.7913
3021/3021 [==============================] - 0s 134us/sample - loss: 0.7413 - mse: 0.7413 - val_loss: 0.0773 - val_mse: 0.0773
Epoch 44/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.6786 - mse: 0.6786
3021/3021 [==============================] - 1s 181us/sample - loss: 0.7008 - mse: 0.7008 - val_loss: 0.0696 - val_mse: 0.0696
Epoch 45/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.6880 - mse: 0.6880
3021/3021 [==============================] - 0s 151us/sample - loss: 0.7558 - mse: 0.7558 - val_loss: 0.0724 - val_mse: 0.0724
Epoch 46/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.5994 - mse: 0.5994
3021/3021 [==============================] - 0s 138us/sample - loss: 0.7062 - mse: 0.7062 - val_loss: 0.0613 - val_mse: 0.0613
Epoch 47/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.7807 - mse: 0.7807
3021/3021 [==============================] - 0s 142us/sample - loss: 0.7453 - mse: 0.7453 - val_loss: 0.0542 - val_mse: 0.0542
Epoch 48/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.6829 - mse: 0.6829
3021/3021 [==============================] - 0s 139us/sample - loss: 0.6898 - mse: 0.6898 - val_loss: 0.0848 - val_mse: 0.0848
Epoch 49/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.6832 - mse: 0.6832
3021/3021 [==============================] - 0s 132us/sample - loss: 0.7094 - mse: 0.7094 - val_loss: 0.0759 - val_mse: 0.0759
Epoch 50/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.7279 - mse: 0.7279
3021/3021 [==============================] - 0s 131us/sample - loss: 0.7246 - mse: 0.7246 - val_loss: 0.0765 - val_mse: 0.0765
Epoch 51/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.6857 - mse: 0.6857
3021/3021 [==============================] - 0s 139us/sample - loss: 0.6763 - mse: 0.6763 - val_loss: 0.0756 - val_mse: 0.0756
Epoch 52/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.6767 - mse: 0.6767
3021/3021 [==============================] - 0s 130us/sample - loss: 0.6859 - mse: 0.6859 - val_loss: 0.0626 - val_mse: 0.0626
Epoch 53/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.6623 - mse: 0.6623
3021/3021 [==============================] - 0s 131us/sample - loss: 0.6830 - mse: 0.6830 - val_loss: 0.0703 - val_mse: 0.0703
Epoch 54/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.7024 - mse: 0.7024
3021/3021 [==============================] - 0s 143us/sample - loss: 0.6738 - mse: 0.6738 - val_loss: 0.0815 - val_mse: 0.0815
Epoch 55/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.7036 - mse: 0.7036
3021/3021 [==============================] - 0s 135us/sample - loss: 0.6651 - mse: 0.6651 - val_loss: 0.0740 - val_mse: 0.0740
Epoch 56/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.7104 - mse: 0.7104
3021/3021 [==============================] - 0s 139us/sample - loss: 0.6743 - mse: 0.6743 - val_loss: 0.0520 - val_mse: 0.0520
Epoch 57/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.6753 - mse: 0.6753
3021/3021 [==============================] - 0s 137us/sample - loss: 0.6754 - mse: 0.6754 - val_loss: 0.0679 - val_mse: 0.0679
Epoch 58/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.7473 - mse: 0.7473
3021/3021 [==============================] - 0s 134us/sample - loss: 0.6732 - mse: 0.6732 - val_loss: 0.0719 - val_mse: 0.0719
Epoch 59/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.5763 - mse: 0.5763
3021/3021 [==============================] - 0s 139us/sample - loss: 0.6503 - mse: 0.6503 - val_loss: 0.0645 - val_mse: 0.0645
Epoch 60/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.6962 - mse: 0.6962
3021/3021 [==============================] - 0s 140us/sample - loss: 0.6768 - mse: 0.6768 - val_loss: 0.0573 - val_mse: 0.0573
Epoch 61/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.6575 - mse: 0.6575
3021/3021 [==============================] - 0s 149us/sample - loss: 0.6520 - mse: 0.6520 - val_loss: 0.0677 - val_mse: 0.0677
Epoch 62/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.6194 - mse: 0.6194
3021/3021 [==============================] - 0s 139us/sample - loss: 0.6264 - mse: 0.6264 - val_loss: 0.0564 - val_mse: 0.0564
Epoch 63/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.6292 - mse: 0.6292
3021/3021 [==============================] - 0s 142us/sample - loss: 0.6383 - mse: 0.6383 - val_loss: 0.0606 - val_mse: 0.0606
Epoch 64/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.6779 - mse: 0.6779
3021/3021 [==============================] - 0s 134us/sample - loss: 0.6689 - mse: 0.6689 - val_loss: 0.0662 - val_mse: 0.0662
Epoch 65/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.6343 - mse: 0.6343
3021/3021 [==============================] - 0s 133us/sample - loss: 0.6488 - mse: 0.6488 - val_loss: 0.0569 - val_mse: 0.0569
Epoch 66/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.7167 - mse: 0.7167
3021/3021 [==============================] - 0s 146us/sample - loss: 0.6416 - mse: 0.6416 - val_loss: 0.0594 - val_mse: 0.0594
Epoch 67/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.6504 - mse: 0.6504
3021/3021 [==============================] - 0s 141us/sample - loss: 0.6456 - mse: 0.6456 - val_loss: 0.0558 - val_mse: 0.0558
Epoch 68/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.6701 - mse: 0.6701
3021/3021 [==============================] - 0s 139us/sample - loss: 0.6347 - mse: 0.6347 - val_loss: 0.0469 - val_mse: 0.0469
Epoch 69/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.6047 - mse: 0.6047
3021/3021 [==============================] - 0s 138us/sample - loss: 0.5961 - mse: 0.5961 - val_loss: 0.0649 - val_mse: 0.0649
Epoch 70/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.5224 - mse: 0.5224
3021/3021 [==============================] - 0s 135us/sample - loss: 0.5977 - mse: 0.5977 - val_loss: 0.0627 - val_mse: 0.0627
Epoch 71/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.5457 - mse: 0.5457
3021/3021 [==============================] - 0s 142us/sample - loss: 0.6034 - mse: 0.6034 - val_loss: 0.0568 - val_mse: 0.0568
Epoch 72/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.6049 - mse: 0.6049
3021/3021 [==============================] - 0s 136us/sample - loss: 0.6030 - mse: 0.6030 - val_loss: 0.0544 - val_mse: 0.0544
Epoch 73/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.6085 - mse: 0.6085
3021/3021 [==============================] - 0s 134us/sample - loss: 0.6022 - mse: 0.6022 - val_loss: 0.0666 - val_mse: 0.0666
Epoch 74/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.6042 - mse: 0.6042
3021/3021 [==============================] - 0s 135us/sample - loss: 0.5875 - mse: 0.5875 - val_loss: 0.0570 - val_mse: 0.0570
Epoch 75/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.6127 - mse: 0.6127
3021/3021 [==============================] - 0s 136us/sample - loss: 0.5809 - mse: 0.5809 - val_loss: 0.0535 - val_mse: 0.0535
Epoch 76/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.6123 - mse: 0.6123
3021/3021 [==============================] - 0s 130us/sample - loss: 0.6147 - mse: 0.6147 - val_loss: 0.0777 - val_mse: 0.0777
Epoch 77/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.6004 - mse: 0.6004
3021/3021 [==============================] - 0s 131us/sample - loss: 0.6249 - mse: 0.6249 - val_loss: 0.0690 - val_mse: 0.0690
Epoch 78/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.6256 - mse: 0.6256
3021/3021 [==============================] - 0s 144us/sample - loss: 0.6022 - mse: 0.6022 - val_loss: 0.0556 - val_mse: 0.0556
Epoch 79/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.5465 - mse: 0.5465
3021/3021 [==============================] - 0s 140us/sample - loss: 0.6127 - mse: 0.6127 - val_loss: 0.0654 - val_mse: 0.0654
Epoch 80/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.6147 - mse: 0.6147
3021/3021 [==============================] - 0s 131us/sample - loss: 0.6234 - mse: 0.6234 - val_loss: 0.0753 - val_mse: 0.0753
Epoch 81/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.5321 - mse: 0.5321
3021/3021 [==============================] - 0s 136us/sample - loss: 0.5597 - mse: 0.5597 - val_loss: 0.0716 - val_mse: 0.0716
Epoch 82/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.5903 - mse: 0.5903
3021/3021 [==============================] - 0s 139us/sample - loss: 0.5703 - mse: 0.5703 - val_loss: 0.0643 - val_mse: 0.0643
Epoch 83/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.5181 - mse: 0.5181
3021/3021 [==============================] - 0s 140us/sample - loss: 0.5398 - mse: 0.5398 - val_loss: 0.0597 - val_mse: 0.0597
Epoch 84/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.5963 - mse: 0.5963
3021/3021 [==============================] - 0s 136us/sample - loss: 0.5694 - mse: 0.5694 - val_loss: 0.0497 - val_mse: 0.0497
Epoch 85/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.6122 - mse: 0.6122
3021/3021 [==============================] - 0s 136us/sample - loss: 0.5632 - mse: 0.5632 - val_loss: 0.0654 - val_mse: 0.0654
Epoch 86/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.5628 - mse: 0.5628
3021/3021 [==============================] - 0s 140us/sample - loss: 0.5686 - mse: 0.5686 - val_loss: 0.0855 - val_mse: 0.0855
Epoch 87/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.5795 - mse: 0.5795
3021/3021 [==============================] - 0s 133us/sample - loss: 0.5797 - mse: 0.5797 - val_loss: 0.0607 - val_mse: 0.0607
Epoch 88/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.5881 - mse: 0.5881
3021/3021 [==============================] - 0s 135us/sample - loss: 0.5852 - mse: 0.5852 - val_loss: 0.0692 - val_mse: 0.0692
Epoch 89/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.5728 - mse: 0.5728
3021/3021 [==============================] - 0s 138us/sample - loss: 0.5571 - mse: 0.5571 - val_loss: 0.0832 - val_mse: 0.0832
Epoch 90/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.5304 - mse: 0.5304
3021/3021 [==============================] - 0s 151us/sample - loss: 0.5348 - mse: 0.5348 - val_loss: 0.0552 - val_mse: 0.0552
Epoch 91/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.5431 - mse: 0.5431
3021/3021 [==============================] - 0s 138us/sample - loss: 0.5495 - mse: 0.5495 - val_loss: 0.0512 - val_mse: 0.0512
Epoch 92/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.5900 - mse: 0.5900
3021/3021 [==============================] - 0s 129us/sample - loss: 0.5468 - mse: 0.5468 - val_loss: 0.0928 - val_mse: 0.0928
Epoch 93/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.5788 - mse: 0.5788
3021/3021 [==============================] - 0s 145us/sample - loss: 0.5448 - mse: 0.5448 - val_loss: 0.0562 - val_mse: 0.0562
Epoch 94/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.5657 - mse: 0.5657
3021/3021 [==============================] - 0s 144us/sample - loss: 0.6037 - mse: 0.6037 - val_loss: 0.0626 - val_mse: 0.0626
Epoch 95/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.5088 - mse: 0.5088
3021/3021 [==============================] - 0s 136us/sample - loss: 0.5356 - mse: 0.5356 - val_loss: 0.0629 - val_mse: 0.0629
Epoch 96/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.5190 - mse: 0.5190
3021/3021 [==============================] - 0s 133us/sample - loss: 0.5475 - mse: 0.5475 - val_loss: 0.0705 - val_mse: 0.0705
Epoch 97/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.5392 - mse: 0.5392
3021/3021 [==============================] - 0s 137us/sample - loss: 0.5803 - mse: 0.5803 - val_loss: 0.0633 - val_mse: 0.0633
Epoch 98/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.5004 - mse: 0.5004
3021/3021 [==============================] - 0s 142us/sample - loss: 0.5381 - mse: 0.5381 - val_loss: 0.0649 - val_mse: 0.0649
Epoch 99/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.5964 - mse: 0.5964
3021/3021 [==============================] - 0s 152us/sample - loss: 0.5822 - mse: 0.5822 - val_loss: 0.0609 - val_mse: 0.0609
Epoch 100/100
500/3021 [===>..........................] - ETA: 0s - loss: 0.5484 - mse: 0.5484
3021/3021 [==============================] - 0s 151us/sample - loss: 0.5341 - mse: 0.5341 - val_loss: 0.0704 - val_mse: 0.0704Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-05-04T00-59-44Z
Training run 17/46 (flags = list(392, 392, 1e-04, 500, 30, "relu", "relu", 0.05, 0.2))
Using run directory runs/2020-05-04T01-00-31Z
> FLAGS <- flags(
+ flag_numeric("nodes1", 128),
+ flag_numeric("nodes2", 128),
+ flag_numeric("batch_size", 100),
+ flag_string("activation1" .... [TRUNCATED]
> model = keras_model_sequential()
> model %>%
+ layer_dense(units=FLAGS$nodes1, activation=FLAGS$activation1, input_shape=dim(efw_train2)[2]) %>%
+ layer_dropout(FLAGS$dropout1) %> .... [TRUNCATED]
> model %>% compile(
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ loss = 'mse',
+ metrics = c('mse')
+ )
> model %>% fit(
+ as.matrix(efw_train2), train2Label,
+ epochs=FLAGS$epochs,
+ batch_size=FLAGS$batch_size,
+ validation_data=list(as.matrix( .... [TRUNCATED]
Train on 3021 samples, validate on 334 samples
Epoch 1/30
500/3021 [===>..........................] - ETA: 1s - loss: 42.4563 - mse: 42.4563
3021/3021 [==============================] - 1s 244us/sample - loss: 41.4409 - mse: 41.4409 - val_loss: 40.6402 - val_mse: 40.6402
Epoch 2/30
500/3021 [===>..........................] - ETA: 0s - loss: 40.8095 - mse: 40.8095
3021/3021 [==============================] - 0s 154us/sample - loss: 39.9820 - mse: 39.9820 - val_loss: 39.2545 - val_mse: 39.2545
Epoch 3/30
500/3021 [===>..........................] - ETA: 0s - loss: 38.8327 - mse: 38.8327
3021/3021 [==============================] - 0s 153us/sample - loss: 38.6203 - mse: 38.6203 - val_loss: 37.9134 - val_mse: 37.9134
Epoch 4/30
500/3021 [===>..........................] - ETA: 0s - loss: 37.3722 - mse: 37.3722
3021/3021 [==============================] - 0s 149us/sample - loss: 37.3046 - mse: 37.3046 - val_loss: 36.6240 - val_mse: 36.6240
Epoch 5/30
500/3021 [===>..........................] - ETA: 0s - loss: 36.0150 - mse: 36.0150
3021/3021 [==============================] - 0s 152us/sample - loss: 36.0293 - mse: 36.0293 - val_loss: 35.3789 - val_mse: 35.3789
Epoch 6/30
500/3021 [===>..........................] - ETA: 0s - loss: 35.2379 - mse: 35.2379
3021/3021 [==============================] - 0s 147us/sample - loss: 34.7811 - mse: 34.7811 - val_loss: 34.1877 - val_mse: 34.1877
Epoch 7/30
500/3021 [===>..........................] - ETA: 0s - loss: 33.4206 - mse: 33.4206
3021/3021 [==============================] - 0s 140us/sample - loss: 33.6160 - mse: 33.6160 - val_loss: 33.0134 - val_mse: 33.0134
Epoch 8/30
500/3021 [===>..........................] - ETA: 0s - loss: 32.6019 - mse: 32.6019
3021/3021 [==============================] - 0s 146us/sample - loss: 32.4140 - mse: 32.4140 - val_loss: 31.8671 - val_mse: 31.8671
Epoch 9/30
500/3021 [===>..........................] - ETA: 0s - loss: 31.6098 - mse: 31.6098
3021/3021 [==============================] - 0s 148us/sample - loss: 31.3002 - mse: 31.3002 - val_loss: 30.7517 - val_mse: 30.7517
Epoch 10/30
500/3021 [===>..........................] - ETA: 0s - loss: 30.7239 - mse: 30.7239
3021/3021 [==============================] - 0s 151us/sample - loss: 30.2026 - mse: 30.2026 - val_loss: 29.6625 - val_mse: 29.6625
Epoch 11/30
500/3021 [===>..........................] - ETA: 0s - loss: 29.1217 - mse: 29.1217
3021/3021 [==============================] - 0s 145us/sample - loss: 29.1270 - mse: 29.1270 - val_loss: 28.5996 - val_mse: 28.5996
Epoch 12/30
500/3021 [===>..........................] - ETA: 0s - loss: 27.6927 - mse: 27.6927
3021/3021 [==============================] - 0s 140us/sample - loss: 28.0861 - mse: 28.0861 - val_loss: 27.5567 - val_mse: 27.5567
Epoch 13/30
500/3021 [===>..........................] - ETA: 0s - loss: 27.1420 - mse: 27.1420
3021/3021 [==============================] - 0s 146us/sample - loss: 27.0800 - mse: 27.0800 - val_loss: 26.5456 - val_mse: 26.5456
Epoch 14/30
500/3021 [===>..........................] - ETA: 0s - loss: 26.5851 - mse: 26.5851
3021/3021 [==============================] - 0s 147us/sample - loss: 26.0702 - mse: 26.0702 - val_loss: 25.5625 - val_mse: 25.5625
Epoch 15/30
500/3021 [===>..........................] - ETA: 0s - loss: 25.0596 - mse: 25.0596
3021/3021 [==============================] - 0s 141us/sample - loss: 25.0873 - mse: 25.0873 - val_loss: 24.6188 - val_mse: 24.6188
Epoch 16/30
500/3021 [===>..........................] - ETA: 0s - loss: 24.3235 - mse: 24.3235
3021/3021 [==============================] - 0s 146us/sample - loss: 24.1822 - mse: 24.1822 - val_loss: 23.7000 - val_mse: 23.7000
Epoch 17/30
500/3021 [===>..........................] - ETA: 0s - loss: 23.1981 - mse: 23.1981
3021/3021 [==============================] - 0s 147us/sample - loss: 23.2738 - mse: 23.2738 - val_loss: 22.8042 - val_mse: 22.8042
Epoch 18/30
500/3021 [===>..........................] - ETA: 0s - loss: 22.6888 - mse: 22.6888
3021/3021 [==============================] - 0s 149us/sample - loss: 22.3951 - mse: 22.3951 - val_loss: 21.9459 - val_mse: 21.9459
Epoch 19/30
500/3021 [===>..........................] - ETA: 0s - loss: 21.6252 - mse: 21.6252
3021/3021 [==============================] - 0s 150us/sample - loss: 21.5721 - mse: 21.5721 - val_loss: 21.1206 - val_mse: 21.1206
Epoch 20/30
500/3021 [===>..........................] - ETA: 0s - loss: 20.7162 - mse: 20.7162
3021/3021 [==============================] - 0s 145us/sample - loss: 20.7558 - mse: 20.7558 - val_loss: 20.3297 - val_mse: 20.3297
Epoch 21/30
500/3021 [===>..........................] - ETA: 0s - loss: 20.0079 - mse: 20.0079
3021/3021 [==============================] - 0s 143us/sample - loss: 19.9924 - mse: 19.9924 - val_loss: 19.5721 - val_mse: 19.5721
Epoch 22/30
500/3021 [===>..........................] - ETA: 0s - loss: 19.4584 - mse: 19.4584
3021/3021 [==============================] - 0s 146us/sample - loss: 19.2398 - mse: 19.2398 - val_loss: 18.8469 - val_mse: 18.8469
Epoch 23/30
500/3021 [===>..........................] - ETA: 0s - loss: 19.1979 - mse: 19.1979
3021/3021 [==============================] - 0s 159us/sample - loss: 18.5603 - mse: 18.5603 - val_loss: 18.1573 - val_mse: 18.1573
Epoch 24/30
500/3021 [===>..........................] - ETA: 0s - loss: 18.3479 - mse: 18.3479
3021/3021 [==============================] - 0s 149us/sample - loss: 17.8908 - mse: 17.8908 - val_loss: 17.5057 - val_mse: 17.5057
Epoch 25/30
500/3021 [===>..........................] - ETA: 0s - loss: 17.6079 - mse: 17.6079
3021/3021 [==============================] - 0s 140us/sample - loss: 17.2407 - mse: 17.2407 - val_loss: 16.8861 - val_mse: 16.8861
Epoch 26/30
500/3021 [===>..........................] - ETA: 0s - loss: 16.8221 - mse: 16.8221
3021/3021 [==============================] - 0s 145us/sample - loss: 16.6533 - mse: 16.6533 - val_loss: 16.2944 - val_mse: 16.2944
Epoch 27/30
500/3021 [===>..........................] - ETA: 0s - loss: 16.6278 - mse: 16.6278
2500/3021 [=======================>......] - ETA: 0s - loss: 16.1768 - mse: 16.1768
3021/3021 [==============================] - 0s 157us/sample - loss: 16.0657 - mse: 16.0657 - val_loss: 15.7329 - val_mse: 15.7329
Epoch 28/30
500/3021 [===>..........................] - ETA: 0s - loss: 15.7556 - mse: 15.7556
3021/3021 [==============================] - 0s 149us/sample - loss: 15.5201 - mse: 15.5201 - val_loss: 15.1943 - val_mse: 15.1943
Epoch 29/30
500/3021 [===>..........................] - ETA: 0s - loss: 15.3362 - mse: 15.3362
3000/3021 [============================>.] - ETA: 0s - loss: 15.0089 - mse: 15.0089
3021/3021 [==============================] - 0s 153us/sample - loss: 14.9896 - mse: 14.9896 - val_loss: 14.6850 - val_mse: 14.6850
Epoch 30/30
500/3021 [===>..........................] - ETA: 0s - loss: 14.7176 - mse: 14.7176
3021/3021 [==============================] - 0s 143us/sample - loss: 14.5055 - mse: 14.5055 - val_loss: 14.1979 - val_mse: 14.1979Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-05-04T01-00-31Z
Training run 18/46 (flags = list(64, 128, 0.01, 100, 100, "tanh", "relu", 0.1, 0.2))
Using run directory runs/2020-05-04T01-00-48Z
> FLAGS <- flags(
+ flag_numeric("nodes1", 128),
+ flag_numeric("nodes2", 128),
+ flag_numeric("batch_size", 100),
+ flag_string("activation1" .... [TRUNCATED]
> model = keras_model_sequential()
> model %>%
+ layer_dense(units=FLAGS$nodes1, activation=FLAGS$activation1, input_shape=dim(efw_train2)[2]) %>%
+ layer_dropout(FLAGS$dropout1) %> .... [TRUNCATED]
> model %>% compile(
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ loss = 'mse',
+ metrics = c('mse')
+ )
> model %>% fit(
+ as.matrix(efw_train2), train2Label,
+ epochs=FLAGS$epochs,
+ batch_size=FLAGS$batch_size,
+ validation_data=list(as.matrix( .... [TRUNCATED]
Train on 3021 samples, validate on 334 samples
Epoch 1/100
100/3021 [..............................] - ETA: 7s - loss: 45.4232 - mse: 45.4232
2600/3021 [========================>.....] - ETA: 0s - loss: 16.7872 - mse: 16.7872
3021/3021 [==============================] - 1s 254us/sample - loss: 14.7895 - mse: 14.7895 - val_loss: 1.7331 - val_mse: 1.7331
Epoch 2/100
100/3021 [..............................] - ETA: 0s - loss: 1.4360 - mse: 1.4360
2200/3021 [====================>.........] - ETA: 0s - loss: 0.8978 - mse: 0.8978
3021/3021 [==============================] - 0s 159us/sample - loss: 0.7735 - mse: 0.7735 - val_loss: 0.2410 - val_mse: 0.2410
Epoch 3/100
100/3021 [..............................] - ETA: 0s - loss: 0.3713 - mse: 0.3713
2100/3021 [===================>..........] - ETA: 0s - loss: 0.3028 - mse: 0.3028
3021/3021 [==============================] - 0s 163us/sample - loss: 0.2863 - mse: 0.2863 - val_loss: 0.0952 - val_mse: 0.0952
Epoch 4/100
100/3021 [..............................] - ETA: 0s - loss: 0.2306 - mse: 0.2306
2400/3021 [======================>.......] - ETA: 0s - loss: 0.2119 - mse: 0.2119
3021/3021 [==============================] - 0s 147us/sample - loss: 0.2120 - mse: 0.2120 - val_loss: 0.0901 - val_mse: 0.0901
Epoch 5/100
100/3021 [..............................] - ETA: 0s - loss: 0.2036 - mse: 0.2036
2500/3021 [=======================>......] - ETA: 0s - loss: 0.1982 - mse: 0.1982
3021/3021 [==============================] - 1s 168us/sample - loss: 0.1924 - mse: 0.1924 - val_loss: 0.0585 - val_mse: 0.0585
Epoch 6/100
100/3021 [..............................] - ETA: 0s - loss: 0.1663 - mse: 0.1663
1800/3021 [================>.............] - ETA: 0s - loss: 0.1852 - mse: 0.1852
3021/3021 [==============================] - 0s 157us/sample - loss: 0.1771 - mse: 0.1771 - val_loss: 0.0812 - val_mse: 0.0812
Epoch 7/100
100/3021 [..............................] - ETA: 0s - loss: 0.1808 - mse: 0.1808
2400/3021 [======================>.......] - ETA: 0s - loss: 0.1557 - mse: 0.1557
3021/3021 [==============================] - 0s 161us/sample - loss: 0.1569 - mse: 0.1569 - val_loss: 0.0765 - val_mse: 0.0765
Epoch 8/100
100/3021 [..............................] - ETA: 0s - loss: 0.2044 - mse: 0.2044
2400/3021 [======================>.......] - ETA: 0s - loss: 0.1520 - mse: 0.1520
3021/3021 [==============================] - 0s 150us/sample - loss: 0.1529 - mse: 0.1529 - val_loss: 0.0570 - val_mse: 0.0570
Epoch 9/100
100/3021 [..............................] - ETA: 0s - loss: 0.1491 - mse: 0.1491
1600/3021 [==============>...............] - ETA: 0s - loss: 0.1529 - mse: 0.1529
3021/3021 [==============================] - 0s 165us/sample - loss: 0.1555 - mse: 0.1555 - val_loss: 0.0751 - val_mse: 0.0751
Epoch 10/100
100/3021 [..............................] - ETA: 0s - loss: 0.1342 - mse: 0.1342
1600/3021 [==============>...............] - ETA: 0s - loss: 0.1609 - mse: 0.1609
3021/3021 [==============================] - 0s 163us/sample - loss: 0.1569 - mse: 0.1569 - val_loss: 0.0694 - val_mse: 0.0694
Epoch 11/100
100/3021 [..............................] - ETA: 0s - loss: 0.1405 - mse: 0.1405
2500/3021 [=======================>......] - ETA: 0s - loss: 0.1385 - mse: 0.1385
3021/3021 [==============================] - 1s 168us/sample - loss: 0.1409 - mse: 0.1409 - val_loss: 0.0768 - val_mse: 0.0768
Epoch 12/100
100/3021 [..............................] - ETA: 0s - loss: 0.1442 - mse: 0.1442
1500/3021 [=============>................] - ETA: 0s - loss: 0.1506 - mse: 0.1506
3021/3021 [==============================] - 0s 161us/sample - loss: 0.1562 - mse: 0.1562 - val_loss: 0.0606 - val_mse: 0.0606
Epoch 13/100
100/3021 [..............................] - ETA: 0s - loss: 0.1639 - mse: 0.1639
2100/3021 [===================>..........] - ETA: 0s - loss: 0.1414 - mse: 0.1414
3021/3021 [==============================] - 1s 168us/sample - loss: 0.1372 - mse: 0.1372 - val_loss: 0.0588 - val_mse: 0.0588
Epoch 14/100
100/3021 [..............................] - ETA: 0s - loss: 0.1152 - mse: 0.1152
1600/3021 [==============>...............] - ETA: 0s - loss: 0.1373 - mse: 0.1373
3021/3021 [==============================] - 0s 154us/sample - loss: 0.1440 - mse: 0.1440 - val_loss: 0.1438 - val_mse: 0.1438
Epoch 15/100
100/3021 [..............................] - ETA: 0s - loss: 0.1896 - mse: 0.1896
2000/3021 [==================>...........] - ETA: 0s - loss: 0.1605 - mse: 0.1605
3021/3021 [==============================] - 0s 149us/sample - loss: 0.1502 - mse: 0.1502 - val_loss: 0.0597 - val_mse: 0.0597
Epoch 16/100
100/3021 [..............................] - ETA: 0s - loss: 0.1283 - mse: 0.1283
1800/3021 [================>.............] - ETA: 0s - loss: 0.1490 - mse: 0.1490
3021/3021 [==============================] - 0s 155us/sample - loss: 0.1600 - mse: 0.1600 - val_loss: 0.0934 - val_mse: 0.0934
Epoch 17/100
100/3021 [..............................] - ETA: 0s - loss: 0.1750 - mse: 0.1750
1500/3021 [=============>................] - ETA: 0s - loss: 0.1557 - mse: 0.1557
3021/3021 [==============================] - 0s 163us/sample - loss: 0.1479 - mse: 0.1479 - val_loss: 0.0613 - val_mse: 0.0613
Epoch 18/100
100/3021 [..............................] - ETA: 0s - loss: 0.1303 - mse: 0.1303
2700/3021 [=========================>....] - ETA: 0s - loss: 0.1457 - mse: 0.1457
3021/3021 [==============================] - 0s 152us/sample - loss: 0.1460 - mse: 0.1460 - val_loss: 0.0665 - val_mse: 0.0665
Epoch 19/100
100/3021 [..............................] - ETA: 0s - loss: 0.1115 - mse: 0.1115
1600/3021 [==============>...............] - ETA: 0s - loss: 0.1487 - mse: 0.1487
3021/3021 [==============================] - 0s 165us/sample - loss: 0.1375 - mse: 0.1375 - val_loss: 0.0916 - val_mse: 0.0916
Epoch 20/100
100/3021 [..............................] - ETA: 0s - loss: 0.1446 - mse: 0.1446
2500/3021 [=======================>......] - ETA: 0s - loss: 0.1371 - mse: 0.1371
3021/3021 [==============================] - 0s 161us/sample - loss: 0.1362 - mse: 0.1362 - val_loss: 0.0853 - val_mse: 0.0853
Epoch 21/100
100/3021 [..............................] - ETA: 0s - loss: 0.1416 - mse: 0.1416
2500/3021 [=======================>......] - ETA: 0s - loss: 0.1286 - mse: 0.1286
3021/3021 [==============================] - 0s 148us/sample - loss: 0.1269 - mse: 0.1269 - val_loss: 0.0779 - val_mse: 0.0779
Epoch 22/100
100/3021 [..............................] - ETA: 0s - loss: 0.1647 - mse: 0.1647
2400/3021 [======================>.......] - ETA: 0s - loss: 0.1299 - mse: 0.1299
3021/3021 [==============================] - 0s 160us/sample - loss: 0.1284 - mse: 0.1284 - val_loss: 0.0596 - val_mse: 0.0596
Epoch 23/100
100/3021 [..............................] - ETA: 0s - loss: 0.0979 - mse: 0.0979
2200/3021 [====================>.........] - ETA: 0s - loss: 0.1259 - mse: 0.1259
3021/3021 [==============================] - 0s 159us/sample - loss: 0.1237 - mse: 0.1237 - val_loss: 0.0521 - val_mse: 0.0521
Epoch 24/100
100/3021 [..............................] - ETA: 0s - loss: 0.1113 - mse: 0.1113
2500/3021 [=======================>......] - ETA: 0s - loss: 0.1223 - mse: 0.1223
3021/3021 [==============================] - 0s 157us/sample - loss: 0.1217 - mse: 0.1217 - val_loss: 0.0621 - val_mse: 0.0621
Epoch 25/100
100/3021 [..............................] - ETA: 0s - loss: 0.1211 - mse: 0.1211
2500/3021 [=======================>......] - ETA: 0s - loss: 0.1183 - mse: 0.1183
3021/3021 [==============================] - 0s 155us/sample - loss: 0.1175 - mse: 0.1175 - val_loss: 0.0663 - val_mse: 0.0663
Epoch 26/100
100/3021 [..............................] - ETA: 0s - loss: 0.1014 - mse: 0.1014
2300/3021 [=====================>........] - ETA: 0s - loss: 0.1193 - mse: 0.1193
3021/3021 [==============================] - 1s 171us/sample - loss: 0.1185 - mse: 0.1185 - val_loss: 0.0549 - val_mse: 0.0549
Epoch 27/100
100/3021 [..............................] - ETA: 0s - loss: 0.0820 - mse: 0.0820
1900/3021 [=================>............] - ETA: 0s - loss: 0.1187 - mse: 0.1187
3021/3021 [==============================] - 0s 156us/sample - loss: 0.1146 - mse: 0.1146 - val_loss: 0.0570 - val_mse: 0.0570
Epoch 28/100
100/3021 [..............................] - ETA: 0s - loss: 0.0997 - mse: 0.0997
2200/3021 [====================>.........] - ETA: 0s - loss: 0.1250 - mse: 0.1250
3021/3021 [==============================] - 0s 160us/sample - loss: 0.1233 - mse: 0.1233 - val_loss: 0.0502 - val_mse: 0.0502
Epoch 29/100
100/3021 [..............................] - ETA: 0s - loss: 0.1097 - mse: 0.1097
2200/3021 [====================>.........] - ETA: 0s - loss: 0.1258 - mse: 0.1258
3021/3021 [==============================] - 0s 162us/sample - loss: 0.1272 - mse: 0.1272 - val_loss: 0.0697 - val_mse: 0.0697
Epoch 30/100
100/3021 [..............................] - ETA: 0s - loss: 0.1229 - mse: 0.1229
1900/3021 [=================>............] - ETA: 0s - loss: 0.1192 - mse: 0.1192
3021/3021 [==============================] - 1s 172us/sample - loss: 0.1193 - mse: 0.1193 - val_loss: 0.0775 - val_mse: 0.0775
Epoch 31/100
100/3021 [..............................] - ETA: 0s - loss: 0.1607 - mse: 0.1607
2000/3021 [==================>...........] - ETA: 0s - loss: 0.1106 - mse: 0.1106
3021/3021 [==============================] - 0s 160us/sample - loss: 0.1144 - mse: 0.1144 - val_loss: 0.0785 - val_mse: 0.0785
Epoch 32/100
100/3021 [..............................] - ETA: 0s - loss: 0.1037 - mse: 0.1037
2500/3021 [=======================>......] - ETA: 0s - loss: 0.1159 - mse: 0.1159
3021/3021 [==============================] - 1s 174us/sample - loss: 0.1117 - mse: 0.1117 - val_loss: 0.0502 - val_mse: 0.0502
Epoch 33/100
100/3021 [..............................] - ETA: 0s - loss: 0.1045 - mse: 0.1045
1700/3021 [===============>..............] - ETA: 0s - loss: 0.1057 - mse: 0.1057
3021/3021 [==============================] - 1s 167us/sample - loss: 0.1060 - mse: 0.1060 - val_loss: 0.0863 - val_mse: 0.0863
Epoch 34/100
100/3021 [..............................] - ETA: 0s - loss: 0.1040 - mse: 0.1040
2400/3021 [======================>.......] - ETA: 0s - loss: 0.1126 - mse: 0.1126
3021/3021 [==============================] - 1s 170us/sample - loss: 0.1102 - mse: 0.1102 - val_loss: 0.0918 - val_mse: 0.0918
Epoch 35/100
100/3021 [..............................] - ETA: 0s - loss: 0.1567 - mse: 0.1567
1500/3021 [=============>................] - ETA: 0s - loss: 0.1188 - mse: 0.1188
3021/3021 [==============================] - 0s 154us/sample - loss: 0.1112 - mse: 0.1112 - val_loss: 0.0675 - val_mse: 0.0675
Epoch 36/100
100/3021 [..............................] - ETA: 0s - loss: 0.1055 - mse: 0.1055
2500/3021 [=======================>......] - ETA: 0s - loss: 0.1089 - mse: 0.1089
3021/3021 [==============================] - 0s 151us/sample - loss: 0.1073 - mse: 0.1073 - val_loss: 0.0501 - val_mse: 0.0501
Epoch 37/100
100/3021 [..............................] - ETA: 0s - loss: 0.1372 - mse: 0.1372
2600/3021 [========================>.....] - ETA: 0s - loss: 0.1154 - mse: 0.1154
3021/3021 [==============================] - 0s 149us/sample - loss: 0.1132 - mse: 0.1132 - val_loss: 0.0687 - val_mse: 0.0687
Epoch 38/100
100/3021 [..............................] - ETA: 0s - loss: 0.1354 - mse: 0.1354
2200/3021 [====================>.........] - ETA: 0s - loss: 0.1113 - mse: 0.1113
3021/3021 [==============================] - 0s 159us/sample - loss: 0.1106 - mse: 0.1106 - val_loss: 0.0563 - val_mse: 0.0563
Epoch 39/100
100/3021 [..............................] - ETA: 0s - loss: 0.1235 - mse: 0.1235
2100/3021 [===================>..........] - ETA: 0s - loss: 0.1072 - mse: 0.1072
3021/3021 [==============================] - 0s 157us/sample - loss: 0.1051 - mse: 0.1052 - val_loss: 0.0514 - val_mse: 0.0514
Epoch 40/100
100/3021 [..............................] - ETA: 0s - loss: 0.1091 - mse: 0.1091
1800/3021 [================>.............] - ETA: 0s - loss: 0.1087 - mse: 0.1087
3021/3021 [==============================] - 1s 175us/sample - loss: 0.1022 - mse: 0.1022 - val_loss: 0.0594 - val_mse: 0.0594
Epoch 41/100
100/3021 [..............................] - ETA: 0s - loss: 0.0930 - mse: 0.0930
2000/3021 [==================>...........] - ETA: 0s - loss: 0.1084 - mse: 0.1084
3021/3021 [==============================] - 0s 163us/sample - loss: 0.1079 - mse: 0.1079 - val_loss: 0.0921 - val_mse: 0.0921
Epoch 42/100
100/3021 [..............................] - ETA: 0s - loss: 0.1377 - mse: 0.1377
2300/3021 [=====================>........] - ETA: 0s - loss: 0.1149 - mse: 0.1149
3021/3021 [==============================] - 0s 157us/sample - loss: 0.1142 - mse: 0.1142 - val_loss: 0.0519 - val_mse: 0.0519
Epoch 43/100
100/3021 [..............................] - ETA: 0s - loss: 0.0834 - mse: 0.0834
1900/3021 [=================>............] - ETA: 0s - loss: 0.0995 - mse: 0.0995
3021/3021 [==============================] - 0s 160us/sample - loss: 0.1024 - mse: 0.1024 - val_loss: 0.0564 - val_mse: 0.0564
Epoch 44/100
100/3021 [..............................] - ETA: 0s - loss: 0.1115 - mse: 0.1115
2300/3021 [=====================>........] - ETA: 0s - loss: 0.1152 - mse: 0.1152
3021/3021 [==============================] - 0s 156us/sample - loss: 0.1111 - mse: 0.1111 - val_loss: 0.0556 - val_mse: 0.0556
Epoch 45/100
100/3021 [..............................] - ETA: 0s - loss: 0.1091 - mse: 0.1091
2400/3021 [======================>.......] - ETA: 0s - loss: 0.0996 - mse: 0.0996
3021/3021 [==============================] - 0s 161us/sample - loss: 0.1028 - mse: 0.1028 - val_loss: 0.0432 - val_mse: 0.0432
Epoch 46/100
100/3021 [..............................] - ETA: 0s - loss: 0.0891 - mse: 0.0891
1500/3021 [=============>................] - ETA: 0s - loss: 0.0986 - mse: 0.0986
3021/3021 [==============================] - 1s 167us/sample - loss: 0.0953 - mse: 0.0953 - val_loss: 0.0517 - val_mse: 0.0517
Epoch 47/100
100/3021 [..............................] - ETA: 0s - loss: 0.1058 - mse: 0.1058
2600/3021 [========================>.....] - ETA: 0s - loss: 0.0947 - mse: 0.0947
3021/3021 [==============================] - 0s 155us/sample - loss: 0.0953 - mse: 0.0953 - val_loss: 0.0486 - val_mse: 0.0486
Epoch 48/100
100/3021 [..............................] - ETA: 0s - loss: 0.0954 - mse: 0.0954
1400/3021 [============>.................] - ETA: 0s - loss: 0.1001 - mse: 0.1001
3021/3021 [==============================] - 0s 162us/sample - loss: 0.0979 - mse: 0.0979 - val_loss: 0.0472 - val_mse: 0.0472
Epoch 49/100
100/3021 [..............................] - ETA: 0s - loss: 0.1102 - mse: 0.1102
2500/3021 [=======================>......] - ETA: 0s - loss: 0.0934 - mse: 0.0934
3021/3021 [==============================] - 0s 150us/sample - loss: 0.0952 - mse: 0.0952 - val_loss: 0.0518 - val_mse: 0.0518
Epoch 50/100
100/3021 [..............................] - ETA: 0s - loss: 0.0862 - mse: 0.0862
1900/3021 [=================>............] - ETA: 0s - loss: 0.0914 - mse: 0.0914
3021/3021 [==============================] - 1s 166us/sample - loss: 0.0943 - mse: 0.0943 - val_loss: 0.0493 - val_mse: 0.0493
Epoch 51/100
100/3021 [..............................] - ETA: 0s - loss: 0.1155 - mse: 0.1155
2200/3021 [====================>.........] - ETA: 0s - loss: 0.0934 - mse: 0.0934
3021/3021 [==============================] - 0s 158us/sample - loss: 0.0946 - mse: 0.0946 - val_loss: 0.0474 - val_mse: 0.0474
Epoch 52/100
100/3021 [..............................] - ETA: 0s - loss: 0.0940 - mse: 0.0940
2600/3021 [========================>.....] - ETA: 0s - loss: 0.0946 - mse: 0.0946
3021/3021 [==============================] - 0s 154us/sample - loss: 0.0948 - mse: 0.0948 - val_loss: 0.0516 - val_mse: 0.0516
Epoch 53/100
100/3021 [..............................] - ETA: 0s - loss: 0.1057 - mse: 0.1057
1900/3021 [=================>............] - ETA: 0s - loss: 0.0961 - mse: 0.0961
3021/3021 [==============================] - 0s 164us/sample - loss: 0.0956 - mse: 0.0956 - val_loss: 0.0492 - val_mse: 0.0492
Epoch 54/100
100/3021 [..............................] - ETA: 0s - loss: 0.1126 - mse: 0.1126
2000/3021 [==================>...........] - ETA: 0s - loss: 0.0964 - mse: 0.0964
3021/3021 [==============================] - 1s 172us/sample - loss: 0.0942 - mse: 0.0942 - val_loss: 0.0496 - val_mse: 0.0496
Epoch 55/100
100/3021 [..............................] - ETA: 0s - loss: 0.0855 - mse: 0.0855
2400/3021 [======================>.......] - ETA: 0s - loss: 0.0912 - mse: 0.0912
3021/3021 [==============================] - 0s 163us/sample - loss: 0.0911 - mse: 0.0911 - val_loss: 0.0521 - val_mse: 0.0521
Epoch 56/100
100/3021 [..............................] - ETA: 0s - loss: 0.1162 - mse: 0.1162
1400/3021 [============>.................] - ETA: 0s - loss: 0.1034 - mse: 0.1034
3021/3021 [==============================] - 1s 170us/sample - loss: 0.0978 - mse: 0.0978 - val_loss: 0.0551 - val_mse: 0.0551
Epoch 57/100
100/3021 [..............................] - ETA: 0s - loss: 0.0785 - mse: 0.0785
1800/3021 [================>.............] - ETA: 0s - loss: 0.0970 - mse: 0.0970
3021/3021 [==============================] - 0s 149us/sample - loss: 0.1004 - mse: 0.1004 - val_loss: 0.0606 - val_mse: 0.0606
Epoch 58/100
100/3021 [..............................] - ETA: 0s - loss: 0.1248 - mse: 0.1248
2700/3021 [=========================>....] - ETA: 0s - loss: 0.0986 - mse: 0.0986
3021/3021 [==============================] - 0s 141us/sample - loss: 0.0974 - mse: 0.0974 - val_loss: 0.0555 - val_mse: 0.0555
Epoch 59/100
100/3021 [..............................] - ETA: 0s - loss: 0.1048 - mse: 0.1048
2700/3021 [=========================>....] - ETA: 0s - loss: 0.0939 - mse: 0.0939
3021/3021 [==============================] - 0s 155us/sample - loss: 0.0928 - mse: 0.0928 - val_loss: 0.0490 - val_mse: 0.0490
Epoch 60/100
100/3021 [..............................] - ETA: 0s - loss: 0.1076 - mse: 0.1076
2200/3021 [====================>.........] - ETA: 0s - loss: 0.0930 - mse: 0.0930
3021/3021 [==============================] - 0s 155us/sample - loss: 0.0931 - mse: 0.0931 - val_loss: 0.0530 - val_mse: 0.0530
Epoch 61/100
100/3021 [..............................] - ETA: 0s - loss: 0.0934 - mse: 0.0934
2600/3021 [========================>.....] - ETA: 0s - loss: 0.0939 - mse: 0.0939
3021/3021 [==============================] - 0s 155us/sample - loss: 0.0922 - mse: 0.0922 - val_loss: 0.0537 - val_mse: 0.0537
Epoch 62/100
100/3021 [..............................] - ETA: 0s - loss: 0.0823 - mse: 0.0823
1700/3021 [===============>..............] - ETA: 0s - loss: 0.0919 - mse: 0.0919
3021/3021 [==============================] - 0s 151us/sample - loss: 0.0948 - mse: 0.0948 - val_loss: 0.0518 - val_mse: 0.0518
Epoch 63/100
100/3021 [..............................] - ETA: 0s - loss: 0.0905 - mse: 0.0905
2800/3021 [==========================>...] - ETA: 0s - loss: 0.0893 - mse: 0.0893
3021/3021 [==============================] - 0s 148us/sample - loss: 0.0891 - mse: 0.0891 - val_loss: 0.0473 - val_mse: 0.0473
Epoch 64/100
100/3021 [..............................] - ETA: 0s - loss: 0.0936 - mse: 0.0936
2700/3021 [=========================>....] - ETA: 0s - loss: 0.0967 - mse: 0.0967
3021/3021 [==============================] - 0s 152us/sample - loss: 0.0965 - mse: 0.0965 - val_loss: 0.0447 - val_mse: 0.0447
Epoch 65/100
100/3021 [..............................] - ETA: 0s - loss: 0.1034 - mse: 0.1034
1700/3021 [===============>..............] - ETA: 0s - loss: 0.0865 - mse: 0.0865
3021/3021 [==============================] - 0s 154us/sample - loss: 0.0914 - mse: 0.0914 - val_loss: 0.0619 - val_mse: 0.0619
Epoch 66/100
100/3021 [..............................] - ETA: 0s - loss: 0.0756 - mse: 0.0756
1700/3021 [===============>..............] - ETA: 0s - loss: 0.0934 - mse: 0.0934
3021/3021 [==============================] - 0s 156us/sample - loss: 0.0952 - mse: 0.0952 - val_loss: 0.0470 - val_mse: 0.0470
Epoch 67/100
100/3021 [..............................] - ETA: 0s - loss: 0.0881 - mse: 0.0881
1500/3021 [=============>................] - ETA: 0s - loss: 0.0882 - mse: 0.0882
3021/3021 [==============================] - 0s 158us/sample - loss: 0.0852 - mse: 0.0852 - val_loss: 0.0481 - val_mse: 0.0481
Epoch 68/100
100/3021 [..............................] - ETA: 0s - loss: 0.0744 - mse: 0.0744
2300/3021 [=====================>........] - ETA: 0s - loss: 0.0882 - mse: 0.0882
3021/3021 [==============================] - 0s 146us/sample - loss: 0.0874 - mse: 0.0874 - val_loss: 0.0483 - val_mse: 0.0483
Epoch 69/100
100/3021 [..............................] - ETA: 0s - loss: 0.0963 - mse: 0.0963
1800/3021 [================>.............] - ETA: 0s - loss: 0.0783 - mse: 0.0783
3021/3021 [==============================] - 0s 150us/sample - loss: 0.0790 - mse: 0.0790 - val_loss: 0.0522 - val_mse: 0.0522
Epoch 70/100
100/3021 [..............................] - ETA: 0s - loss: 0.0730 - mse: 0.0730
2700/3021 [=========================>....] - ETA: 0s - loss: 0.0837 - mse: 0.0837
3021/3021 [==============================] - 0s 145us/sample - loss: 0.0832 - mse: 0.0832 - val_loss: 0.0416 - val_mse: 0.0416
Epoch 71/100
100/3021 [..............................] - ETA: 0s - loss: 0.0638 - mse: 0.0638
2400/3021 [======================>.......] - ETA: 0s - loss: 0.0808 - mse: 0.0808
3021/3021 [==============================] - 0s 152us/sample - loss: 0.0801 - mse: 0.0801 - val_loss: 0.0442 - val_mse: 0.0442
Epoch 72/100
100/3021 [..............................] - ETA: 0s - loss: 0.1118 - mse: 0.1118
2700/3021 [=========================>....] - ETA: 0s - loss: 0.0845 - mse: 0.0845
3021/3021 [==============================] - 0s 161us/sample - loss: 0.0824 - mse: 0.0824 - val_loss: 0.0437 - val_mse: 0.0437
Epoch 73/100
100/3021 [..............................] - ETA: 0s - loss: 0.0934 - mse: 0.0934
1300/3021 [===========>..................] - ETA: 0s - loss: 0.0877 - mse: 0.0877
3021/3021 [==============================] - 0s 157us/sample - loss: 0.0907 - mse: 0.0907 - val_loss: 0.0395 - val_mse: 0.0395
Epoch 74/100
100/3021 [..............................] - ETA: 0s - loss: 0.0756 - mse: 0.0756
2500/3021 [=======================>......] - ETA: 0s - loss: 0.0836 - mse: 0.0836
3021/3021 [==============================] - 0s 154us/sample - loss: 0.0829 - mse: 0.0829 - val_loss: 0.0466 - val_mse: 0.0466
Epoch 75/100
100/3021 [..............................] - ETA: 0s - loss: 0.0916 - mse: 0.0916
1700/3021 [===============>..............] - ETA: 0s - loss: 0.0796 - mse: 0.0796
3021/3021 [==============================] - 0s 155us/sample - loss: 0.0793 - mse: 0.0793 - val_loss: 0.0463 - val_mse: 0.0463
Epoch 76/100
100/3021 [..............................] - ETA: 0s - loss: 0.0617 - mse: 0.0617
2500/3021 [=======================>......] - ETA: 0s - loss: 0.0833 - mse: 0.0833
3021/3021 [==============================] - 0s 157us/sample - loss: 0.0824 - mse: 0.0824 - val_loss: 0.0535 - val_mse: 0.0535
Epoch 77/100
100/3021 [..............................] - ETA: 0s - loss: 0.0784 - mse: 0.0784
2300/3021 [=====================>........] - ETA: 0s - loss: 0.0901 - mse: 0.0901
3021/3021 [==============================] - 0s 155us/sample - loss: 0.0888 - mse: 0.0888 - val_loss: 0.0425 - val_mse: 0.0425
Epoch 78/100
100/3021 [..............................] - ETA: 0s - loss: 0.0622 - mse: 0.0622
1500/3021 [=============>................] - ETA: 0s - loss: 0.0874 - mse: 0.0874
3021/3021 [==============================] - 1s 175us/sample - loss: 0.0870 - mse: 0.0870 - val_loss: 0.0548 - val_mse: 0.0548
Epoch 79/100
100/3021 [..............................] - ETA: 0s - loss: 0.0859 - mse: 0.0859
2300/3021 [=====================>........] - ETA: 0s - loss: 0.0882 - mse: 0.0882
3021/3021 [==============================] - 0s 160us/sample - loss: 0.0858 - mse: 0.0858 - val_loss: 0.0588 - val_mse: 0.0588
Epoch 80/100
100/3021 [..............................] - ETA: 0s - loss: 0.0772 - mse: 0.0772
2400/3021 [======================>.......] - ETA: 0s - loss: 0.0822 - mse: 0.0822
3021/3021 [==============================] - 1s 277us/sample - loss: 0.0830 - mse: 0.0830 - val_loss: 0.0453 - val_mse: 0.0453
Epoch 81/100
100/3021 [..............................] - ETA: 0s - loss: 0.0761 - mse: 0.0761
2000/3021 [==================>...........] - ETA: 0s - loss: 0.0834 - mse: 0.0834
3021/3021 [==============================] - 0s 154us/sample - loss: 0.0815 - mse: 0.0815 - val_loss: 0.0550 - val_mse: 0.0550
Epoch 82/100
100/3021 [..............................] - ETA: 0s - loss: 0.0842 - mse: 0.0842
2200/3021 [====================>.........] - ETA: 0s - loss: 0.0835 - mse: 0.0835
3021/3021 [==============================] - 0s 151us/sample - loss: 0.0815 - mse: 0.0815 - val_loss: 0.0418 - val_mse: 0.0418
Epoch 83/100
100/3021 [..............................] - ETA: 0s - loss: 0.0791 - mse: 0.0791
1800/3021 [================>.............] - ETA: 0s - loss: 0.0774 - mse: 0.0774
3000/3021 [============================>.] - ETA: 0s - loss: 0.0765 - mse: 0.0765
3021/3021 [==============================] - 1s 193us/sample - loss: 0.0765 - mse: 0.0765 - val_loss: 0.0418 - val_mse: 0.0418
Epoch 84/100
100/3021 [..............................] - ETA: 0s - loss: 0.0855 - mse: 0.0855
2300/3021 [=====================>........] - ETA: 0s - loss: 0.0836 - mse: 0.0836
3021/3021 [==============================] - 0s 162us/sample - loss: 0.0827 - mse: 0.0827 - val_loss: 0.0436 - val_mse: 0.0436
Epoch 85/100
100/3021 [..............................] - ETA: 0s - loss: 0.0716 - mse: 0.0716
2100/3021 [===================>..........] - ETA: 0s - loss: 0.0804 - mse: 0.0804
3021/3021 [==============================] - 0s 162us/sample - loss: 0.0833 - mse: 0.0833 - val_loss: 0.0406 - val_mse: 0.0406
Epoch 86/100
100/3021 [..............................] - ETA: 0s - loss: 0.0813 - mse: 0.0813
1200/3021 [==========>...................] - ETA: 0s - loss: 0.0739 - mse: 0.0739
2900/3021 [===========================>..] - ETA: 0s - loss: 0.0756 - mse: 0.0756
3021/3021 [==============================] - 1s 196us/sample - loss: 0.0757 - mse: 0.0757 - val_loss: 0.0410 - val_mse: 0.0410
Epoch 87/100
100/3021 [..............................] - ETA: 0s - loss: 0.0642 - mse: 0.0642
2400/3021 [======================>.......] - ETA: 0s - loss: 0.0749 - mse: 0.0749
3021/3021 [==============================] - 0s 161us/sample - loss: 0.0743 - mse: 0.0743 - val_loss: 0.0602 - val_mse: 0.0602
Epoch 88/100
100/3021 [..............................] - ETA: 0s - loss: 0.0922 - mse: 0.0922
1300/3021 [===========>..................] - ETA: 0s - loss: 0.0869 - mse: 0.0869
3021/3021 [==============================] - 0s 158us/sample - loss: 0.0842 - mse: 0.0842 - val_loss: 0.0362 - val_mse: 0.0362
Epoch 89/100
100/3021 [..............................] - ETA: 0s - loss: 0.0651 - mse: 0.0651
2300/3021 [=====================>........] - ETA: 0s - loss: 0.0798 - mse: 0.0798
3021/3021 [==============================] - 0s 157us/sample - loss: 0.0855 - mse: 0.0855 - val_loss: 0.0484 - val_mse: 0.0484
Epoch 90/100
100/3021 [..............................] - ETA: 0s - loss: 0.0682 - mse: 0.0682
2600/3021 [========================>.....] - ETA: 0s - loss: 0.0761 - mse: 0.0761
3021/3021 [==============================] - 0s 153us/sample - loss: 0.0773 - mse: 0.0773 - val_loss: 0.0388 - val_mse: 0.0388
Epoch 91/100
100/3021 [..............................] - ETA: 0s - loss: 0.0717 - mse: 0.0717
2000/3021 [==================>...........] - ETA: 0s - loss: 0.0786 - mse: 0.0786
3021/3021 [==============================] - 0s 164us/sample - loss: 0.0792 - mse: 0.0792 - val_loss: 0.0436 - val_mse: 0.0436
Epoch 92/100
100/3021 [..............................] - ETA: 0s - loss: 0.0907 - mse: 0.0907
2700/3021 [=========================>....] - ETA: 0s - loss: 0.0758 - mse: 0.0758
3021/3021 [==============================] - 0s 153us/sample - loss: 0.0764 - mse: 0.0764 - val_loss: 0.0473 - val_mse: 0.0473
Epoch 93/100
100/3021 [..............................] - ETA: 0s - loss: 0.0635 - mse: 0.0635
2600/3021 [========================>.....] - ETA: 0s - loss: 0.0736 - mse: 0.0736
3021/3021 [==============================] - 0s 149us/sample - loss: 0.0744 - mse: 0.0744 - val_loss: 0.0544 - val_mse: 0.0544
Epoch 94/100
100/3021 [..............................] - ETA: 0s - loss: 0.0924 - mse: 0.0924
2400/3021 [======================>.......] - ETA: 0s - loss: 0.0817 - mse: 0.0817
3021/3021 [==============================] - 0s 159us/sample - loss: 0.0819 - mse: 0.0819 - val_loss: 0.0487 - val_mse: 0.0487
Epoch 95/100
100/3021 [..............................] - ETA: 0s - loss: 0.0775 - mse: 0.0775
1500/3021 [=============>................] - ETA: 0s - loss: 0.0731 - mse: 0.0731
3021/3021 [==============================] - 0s 152us/sample - loss: 0.0729 - mse: 0.0729 - val_loss: 0.0513 - val_mse: 0.0513
Epoch 96/100
100/3021 [..............................] - ETA: 0s - loss: 0.0725 - mse: 0.0725
2500/3021 [=======================>......] - ETA: 0s - loss: 0.0731 - mse: 0.0731
3021/3021 [==============================] - 0s 162us/sample - loss: 0.0740 - mse: 0.0740 - val_loss: 0.0526 - val_mse: 0.0526
Epoch 97/100
100/3021 [..............................] - ETA: 0s - loss: 0.0974 - mse: 0.0974
2200/3021 [====================>.........] - ETA: 0s - loss: 0.0838 - mse: 0.0838
3021/3021 [==============================] - 0s 156us/sample - loss: 0.0820 - mse: 0.0820 - val_loss: 0.0575 - val_mse: 0.0575
Epoch 98/100
100/3021 [..............................] - ETA: 0s - loss: 0.0847 - mse: 0.0847
2300/3021 [=====================>........] - ETA: 0s - loss: 0.0790 - mse: 0.0790
3021/3021 [==============================] - 0s 163us/sample - loss: 0.0775 - mse: 0.0775 - val_loss: 0.0481 - val_mse: 0.0481
Epoch 99/100
100/3021 [..............................] - ETA: 0s - loss: 0.0817 - mse: 0.0817
2500/3021 [=======================>......] - ETA: 0s - loss: 0.0721 - mse: 0.0721
3021/3021 [==============================] - 0s 152us/sample - loss: 0.0739 - mse: 0.0739 - val_loss: 0.0678 - val_mse: 0.0678
Epoch 100/100
100/3021 [..............................] - ETA: 0s - loss: 0.0780 - mse: 0.0780
2600/3021 [========================>.....] - ETA: 0s - loss: 0.0790 - mse: 0.0790
3021/3021 [==============================] - 0s 155us/sample - loss: 0.0768 - mse: 0.0768 - val_loss: 0.0488 - val_mse: 0.0488Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-05-04T01-00-48Z
Training run 19/46 (flags = list(128, 64, 0.05, 200, 100, "sigmoid", "sigmoid", 0.05, 0.5))
Using run directory runs/2020-05-04T01-01-40Z
> FLAGS <- flags(
+ flag_numeric("nodes1", 128),
+ flag_numeric("nodes2", 128),
+ flag_numeric("batch_size", 100),
+ flag_string("activation1" .... [TRUNCATED]
> model = keras_model_sequential()
> model %>%
+ layer_dense(units=FLAGS$nodes1, activation=FLAGS$activation1, input_shape=dim(efw_train2)[2]) %>%
+ layer_dropout(FLAGS$dropout1) %> .... [TRUNCATED]
> model %>% compile(
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ loss = 'mse',
+ metrics = c('mse')
+ )
> model %>% fit(
+ as.matrix(efw_train2), train2Label,
+ epochs=FLAGS$epochs,
+ batch_size=FLAGS$batch_size,
+ validation_data=list(as.matrix( .... [TRUNCATED]
Train on 3021 samples, validate on 334 samples
Epoch 1/100
200/3021 [>.............................] - ETA: 3s - loss: 49.1104 - mse: 49.1104
3021/3021 [==============================] - 1s 246us/sample - loss: 9.4889 - mse: 9.4889 - val_loss: 1.3383 - val_mse: 1.3383
Epoch 2/100
200/3021 [>.............................] - ETA: 0s - loss: 1.4013 - mse: 1.4013
3021/3021 [==============================] - 0s 144us/sample - loss: 1.1670 - mse: 1.1670 - val_loss: 0.8296 - val_mse: 0.8296
Epoch 3/100
200/3021 [>.............................] - ETA: 0s - loss: 0.7124 - mse: 0.7124
3021/3021 [==============================] - 0s 158us/sample - loss: 0.3902 - mse: 0.3902 - val_loss: 0.2891 - val_mse: 0.2891
Epoch 4/100
200/3021 [>.............................] - ETA: 0s - loss: 0.2677 - mse: 0.2677
3021/3021 [==============================] - 0s 149us/sample - loss: 0.1932 - mse: 0.1932 - val_loss: 0.1397 - val_mse: 0.1397
Epoch 5/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1439 - mse: 0.1439
3021/3021 [==============================] - 0s 151us/sample - loss: 0.1228 - mse: 0.1228 - val_loss: 0.0890 - val_mse: 0.0890
Epoch 6/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1112 - mse: 0.1112
3021/3021 [==============================] - 0s 147us/sample - loss: 0.0992 - mse: 0.0992 - val_loss: 0.0711 - val_mse: 0.0711
Epoch 7/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0795 - mse: 0.0795
3021/3021 [==============================] - 0s 142us/sample - loss: 0.0874 - mse: 0.0874 - val_loss: 0.0583 - val_mse: 0.0583
Epoch 8/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0731 - mse: 0.0731
3021/3021 [==============================] - 1s 195us/sample - loss: 0.0793 - mse: 0.0793 - val_loss: 0.0519 - val_mse: 0.0519
Epoch 9/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0697 - mse: 0.0697
3000/3021 [============================>.] - ETA: 0s - loss: 0.0752 - mse: 0.0752
3021/3021 [==============================] - 0s 151us/sample - loss: 0.0754 - mse: 0.0754 - val_loss: 0.0520 - val_mse: 0.0520
Epoch 10/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0652 - mse: 0.0652
2600/3021 [========================>.....] - ETA: 0s - loss: 0.0708 - mse: 0.0708
3021/3021 [==============================] - 0s 156us/sample - loss: 0.0727 - mse: 0.0727 - val_loss: 0.0481 - val_mse: 0.0481
Epoch 11/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0752 - mse: 0.0752
3000/3021 [============================>.] - ETA: 0s - loss: 0.0714 - mse: 0.0714
3021/3021 [==============================] - 0s 140us/sample - loss: 0.0711 - mse: 0.0711 - val_loss: 0.0465 - val_mse: 0.0465
Epoch 12/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0653 - mse: 0.0653
3021/3021 [==============================] - 0s 139us/sample - loss: 0.0676 - mse: 0.0676 - val_loss: 0.0497 - val_mse: 0.0497
Epoch 13/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0926 - mse: 0.0926
3021/3021 [==============================] - 0s 139us/sample - loss: 0.0665 - mse: 0.0665 - val_loss: 0.0468 - val_mse: 0.0468
Epoch 14/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0587 - mse: 0.0587
3021/3021 [==============================] - 0s 147us/sample - loss: 0.0644 - mse: 0.0644 - val_loss: 0.0456 - val_mse: 0.0456
Epoch 15/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0664 - mse: 0.0664
3021/3021 [==============================] - 0s 145us/sample - loss: 0.0630 - mse: 0.0630 - val_loss: 0.0486 - val_mse: 0.0486
Epoch 16/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0595 - mse: 0.0595
2800/3021 [==========================>...] - ETA: 0s - loss: 0.0637 - mse: 0.0637
3021/3021 [==============================] - 1s 190us/sample - loss: 0.0628 - mse: 0.0628 - val_loss: 0.0425 - val_mse: 0.0425
Epoch 17/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0607 - mse: 0.0607
2800/3021 [==========================>...] - ETA: 0s - loss: 0.0611 - mse: 0.0611
3021/3021 [==============================] - 0s 155us/sample - loss: 0.0608 - mse: 0.0608 - val_loss: 0.0411 - val_mse: 0.0411
Epoch 18/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0598 - mse: 0.0598
3021/3021 [==============================] - 0s 143us/sample - loss: 0.0624 - mse: 0.0624 - val_loss: 0.0435 - val_mse: 0.0435
Epoch 19/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0573 - mse: 0.0573
3021/3021 [==============================] - 0s 138us/sample - loss: 0.0630 - mse: 0.0630 - val_loss: 0.0500 - val_mse: 0.0500
Epoch 20/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0734 - mse: 0.0734
2800/3021 [==========================>...] - ETA: 0s - loss: 0.0630 - mse: 0.0630
3021/3021 [==============================] - 0s 148us/sample - loss: 0.0631 - mse: 0.0631 - val_loss: 0.0504 - val_mse: 0.0504
Epoch 21/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0672 - mse: 0.0672
3000/3021 [============================>.] - ETA: 0s - loss: 0.0556 - mse: 0.0556
3021/3021 [==============================] - 0s 150us/sample - loss: 0.0557 - mse: 0.0557 - val_loss: 0.0419 - val_mse: 0.0419
Epoch 22/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0602 - mse: 0.0602
2200/3021 [====================>.........] - ETA: 0s - loss: 0.0567 - mse: 0.0567
3021/3021 [==============================] - 0s 148us/sample - loss: 0.0573 - mse: 0.0573 - val_loss: 0.0382 - val_mse: 0.0382
Epoch 23/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0420 - mse: 0.0420
3021/3021 [==============================] - 0s 147us/sample - loss: 0.0579 - mse: 0.0579 - val_loss: 0.0415 - val_mse: 0.0415
Epoch 24/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0401 - mse: 0.0401
3021/3021 [==============================] - 0s 139us/sample - loss: 0.0549 - mse: 0.0549 - val_loss: 0.0484 - val_mse: 0.0484
Epoch 25/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0615 - mse: 0.0615
2800/3021 [==========================>...] - ETA: 0s - loss: 0.0559 - mse: 0.0559
3021/3021 [==============================] - 0s 165us/sample - loss: 0.0564 - mse: 0.0564 - val_loss: 0.0400 - val_mse: 0.0400
Epoch 26/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0410 - mse: 0.0410
2400/3021 [======================>.......] - ETA: 0s - loss: 0.0530 - mse: 0.0530
3021/3021 [==============================] - 0s 158us/sample - loss: 0.0523 - mse: 0.0523 - val_loss: 0.0401 - val_mse: 0.0401
Epoch 27/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0538 - mse: 0.0538
3021/3021 [==============================] - 1s 168us/sample - loss: 0.0535 - mse: 0.0535 - val_loss: 0.0438 - val_mse: 0.0438
Epoch 28/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0483 - mse: 0.0483
2800/3021 [==========================>...] - ETA: 0s - loss: 0.0508 - mse: 0.0508
3021/3021 [==============================] - 0s 153us/sample - loss: 0.0513 - mse: 0.0513 - val_loss: 0.0397 - val_mse: 0.0397
Epoch 29/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0531 - mse: 0.0531
3021/3021 [==============================] - 0s 153us/sample - loss: 0.0516 - mse: 0.0516 - val_loss: 0.0403 - val_mse: 0.0403
Epoch 30/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0487 - mse: 0.0487
3021/3021 [==============================] - 0s 146us/sample - loss: 0.0491 - mse: 0.0491 - val_loss: 0.0370 - val_mse: 0.0370
Epoch 31/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0461 - mse: 0.0461
3021/3021 [==============================] - 0s 144us/sample - loss: 0.0486 - mse: 0.0486 - val_loss: 0.0431 - val_mse: 0.0431
Epoch 32/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0428 - mse: 0.0428
2400/3021 [======================>.......] - ETA: 0s - loss: 0.0490 - mse: 0.0490
3021/3021 [==============================] - 0s 146us/sample - loss: 0.0476 - mse: 0.0476 - val_loss: 0.0396 - val_mse: 0.0396
Epoch 33/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0427 - mse: 0.0427
2600/3021 [========================>.....] - ETA: 0s - loss: 0.0498 - mse: 0.0498
3021/3021 [==============================] - 1s 179us/sample - loss: 0.0501 - mse: 0.0501 - val_loss: 0.0413 - val_mse: 0.0413
Epoch 34/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0451 - mse: 0.0451
3021/3021 [==============================] - 0s 154us/sample - loss: 0.0500 - mse: 0.0500 - val_loss: 0.0378 - val_mse: 0.0378
Epoch 35/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0381 - mse: 0.0381
3021/3021 [==============================] - 0s 154us/sample - loss: 0.0479 - mse: 0.0479 - val_loss: 0.0408 - val_mse: 0.0408
Epoch 36/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0410 - mse: 0.0410
3021/3021 [==============================] - 0s 144us/sample - loss: 0.0457 - mse: 0.0457 - val_loss: 0.0406 - val_mse: 0.0406
Epoch 37/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0468 - mse: 0.0468
3021/3021 [==============================] - 0s 152us/sample - loss: 0.0497 - mse: 0.0497 - val_loss: 0.0379 - val_mse: 0.0379
Epoch 38/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0397 - mse: 0.0397
3021/3021 [==============================] - 0s 149us/sample - loss: 0.0478 - mse: 0.0478 - val_loss: 0.0423 - val_mse: 0.0423
Epoch 39/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0547 - mse: 0.0547
3021/3021 [==============================] - 0s 144us/sample - loss: 0.0480 - mse: 0.0480 - val_loss: 0.0424 - val_mse: 0.0424
Epoch 40/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0484 - mse: 0.0484
3021/3021 [==============================] - 0s 144us/sample - loss: 0.0465 - mse: 0.0465 - val_loss: 0.0361 - val_mse: 0.0361
Epoch 41/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0384 - mse: 0.0384
3021/3021 [==============================] - 0s 140us/sample - loss: 0.0437 - mse: 0.0437 - val_loss: 0.0393 - val_mse: 0.0393
Epoch 42/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0531 - mse: 0.0531
3021/3021 [==============================] - 0s 148us/sample - loss: 0.0422 - mse: 0.0422 - val_loss: 0.0344 - val_mse: 0.0344
Epoch 43/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0441 - mse: 0.0441
2400/3021 [======================>.......] - ETA: 0s - loss: 0.0436 - mse: 0.0436
3021/3021 [==============================] - 0s 154us/sample - loss: 0.0431 - mse: 0.0431 - val_loss: 0.0377 - val_mse: 0.0377
Epoch 44/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0415 - mse: 0.0415
2200/3021 [====================>.........] - ETA: 0s - loss: 0.0453 - mse: 0.0453
3021/3021 [==============================] - 0s 148us/sample - loss: 0.0449 - mse: 0.0449 - val_loss: 0.0354 - val_mse: 0.0354
Epoch 45/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0476 - mse: 0.0476
3021/3021 [==============================] - 0s 135us/sample - loss: 0.0447 - mse: 0.0447 - val_loss: 0.0332 - val_mse: 0.0332
Epoch 46/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0391 - mse: 0.0391
3021/3021 [==============================] - 0s 139us/sample - loss: 0.0427 - mse: 0.0427 - val_loss: 0.0400 - val_mse: 0.0400
Epoch 47/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0464 - mse: 0.0464
3021/3021 [==============================] - 0s 143us/sample - loss: 0.0430 - mse: 0.0430 - val_loss: 0.0413 - val_mse: 0.0413
Epoch 48/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0424 - mse: 0.0424
2600/3021 [========================>.....] - ETA: 0s - loss: 0.0480 - mse: 0.0480
3021/3021 [==============================] - 0s 153us/sample - loss: 0.0486 - mse: 0.0486 - val_loss: 0.0595 - val_mse: 0.0595
Epoch 49/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0622 - mse: 0.0622
1400/3021 [============>.................] - ETA: 0s - loss: 0.0557 - mse: 0.0557
3021/3021 [==============================] - 1s 179us/sample - loss: 0.0480 - mse: 0.0480 - val_loss: 0.0376 - val_mse: 0.0376
Epoch 50/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0374 - mse: 0.0374
2600/3021 [========================>.....] - ETA: 0s - loss: 0.0407 - mse: 0.0407
3021/3021 [==============================] - 0s 153us/sample - loss: 0.0409 - mse: 0.0409 - val_loss: 0.0404 - val_mse: 0.0404
Epoch 51/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0361 - mse: 0.0361
3021/3021 [==============================] - 0s 141us/sample - loss: 0.0461 - mse: 0.0461 - val_loss: 0.0391 - val_mse: 0.0391
Epoch 52/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0388 - mse: 0.0388
3021/3021 [==============================] - 0s 144us/sample - loss: 0.0402 - mse: 0.0402 - val_loss: 0.0339 - val_mse: 0.0339
Epoch 53/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0384 - mse: 0.0384
2400/3021 [======================>.......] - ETA: 0s - loss: 0.0433 - mse: 0.0433
3021/3021 [==============================] - 0s 153us/sample - loss: 0.0432 - mse: 0.0432 - val_loss: 0.0369 - val_mse: 0.0369
Epoch 54/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0368 - mse: 0.0368
3021/3021 [==============================] - 0s 139us/sample - loss: 0.0404 - mse: 0.0404 - val_loss: 0.0506 - val_mse: 0.0506
Epoch 55/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0577 - mse: 0.0577
3021/3021 [==============================] - 0s 138us/sample - loss: 0.0443 - mse: 0.0443 - val_loss: 0.0392 - val_mse: 0.0392
Epoch 56/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0465 - mse: 0.0465
3021/3021 [==============================] - 0s 147us/sample - loss: 0.0443 - mse: 0.0443 - val_loss: 0.0371 - val_mse: 0.0371
Epoch 57/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0395 - mse: 0.0395
3021/3021 [==============================] - 0s 145us/sample - loss: 0.0419 - mse: 0.0419 - val_loss: 0.0402 - val_mse: 0.0402
Epoch 58/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0457 - mse: 0.0457
3021/3021 [==============================] - 0s 154us/sample - loss: 0.0462 - mse: 0.0462 - val_loss: 0.0391 - val_mse: 0.0391
Epoch 59/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0379 - mse: 0.0379
2800/3021 [==========================>...] - ETA: 0s - loss: 0.0407 - mse: 0.0407
3021/3021 [==============================] - 0s 143us/sample - loss: 0.0405 - mse: 0.0405 - val_loss: 0.0377 - val_mse: 0.0377
Epoch 60/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0359 - mse: 0.0359
3021/3021 [==============================] - 0s 144us/sample - loss: 0.0392 - mse: 0.0392 - val_loss: 0.0349 - val_mse: 0.0349
Epoch 61/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0363 - mse: 0.0363
3021/3021 [==============================] - 0s 140us/sample - loss: 0.0373 - mse: 0.0373 - val_loss: 0.0384 - val_mse: 0.0384
Epoch 62/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0367 - mse: 0.0367
2600/3021 [========================>.....] - ETA: 0s - loss: 0.0390 - mse: 0.0390
3021/3021 [==============================] - 0s 160us/sample - loss: 0.0388 - mse: 0.0388 - val_loss: 0.0393 - val_mse: 0.0393
Epoch 63/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0432 - mse: 0.0432
3021/3021 [==============================] - 0s 148us/sample - loss: 0.0414 - mse: 0.0414 - val_loss: 0.0396 - val_mse: 0.0396
Epoch 64/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0367 - mse: 0.0367
2600/3021 [========================>.....] - ETA: 0s - loss: 0.0401 - mse: 0.0401
3021/3021 [==============================] - 0s 148us/sample - loss: 0.0404 - mse: 0.0404 - val_loss: 0.0381 - val_mse: 0.0381
Epoch 65/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0445 - mse: 0.0445
3021/3021 [==============================] - 0s 151us/sample - loss: 0.0387 - mse: 0.0387 - val_loss: 0.0398 - val_mse: 0.0398
Epoch 66/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0341 - mse: 0.0341
3021/3021 [==============================] - 0s 147us/sample - loss: 0.0364 - mse: 0.0364 - val_loss: 0.0423 - val_mse: 0.0423
Epoch 67/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0424 - mse: 0.0424
3021/3021 [==============================] - 0s 151us/sample - loss: 0.0390 - mse: 0.0390 - val_loss: 0.0333 - val_mse: 0.0333
Epoch 68/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0309 - mse: 0.0309
2800/3021 [==========================>...] - ETA: 0s - loss: 0.0366 - mse: 0.0366
3021/3021 [==============================] - 0s 153us/sample - loss: 0.0366 - mse: 0.0366 - val_loss: 0.0337 - val_mse: 0.0337
Epoch 69/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0295 - mse: 0.0295
3021/3021 [==============================] - 0s 149us/sample - loss: 0.0413 - mse: 0.0413 - val_loss: 0.0383 - val_mse: 0.0383
Epoch 70/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0302 - mse: 0.0302
3021/3021 [==============================] - 0s 148us/sample - loss: 0.0404 - mse: 0.0404 - val_loss: 0.0419 - val_mse: 0.0419
Epoch 71/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0346 - mse: 0.0346
3021/3021 [==============================] - 0s 156us/sample - loss: 0.0347 - mse: 0.0347 - val_loss: 0.0358 - val_mse: 0.0358
Epoch 72/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0336 - mse: 0.0336
2800/3021 [==========================>...] - ETA: 0s - loss: 0.0349 - mse: 0.0349
3021/3021 [==============================] - 0s 145us/sample - loss: 0.0345 - mse: 0.0345 - val_loss: 0.0378 - val_mse: 0.0378
Epoch 73/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0329 - mse: 0.0329
3021/3021 [==============================] - 0s 145us/sample - loss: 0.0353 - mse: 0.0353 - val_loss: 0.0370 - val_mse: 0.0370
Epoch 74/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0351 - mse: 0.0351
1800/3021 [================>.............] - ETA: 0s - loss: 0.0397 - mse: 0.0397
3021/3021 [==============================] - 1s 196us/sample - loss: 0.0384 - mse: 0.0384 - val_loss: 0.0360 - val_mse: 0.0360
Epoch 75/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0390 - mse: 0.0390
3021/3021 [==============================] - 0s 154us/sample - loss: 0.0388 - mse: 0.0388 - val_loss: 0.0447 - val_mse: 0.0447
Epoch 76/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0343 - mse: 0.0343
3021/3021 [==============================] - 0s 144us/sample - loss: 0.0384 - mse: 0.0384 - val_loss: 0.0553 - val_mse: 0.0553
Epoch 77/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0530 - mse: 0.0530
3021/3021 [==============================] - 1s 168us/sample - loss: 0.0434 - mse: 0.0434 - val_loss: 0.0482 - val_mse: 0.0482
Epoch 78/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0419 - mse: 0.0419
3021/3021 [==============================] - 0s 157us/sample - loss: 0.0400 - mse: 0.0400 - val_loss: 0.0374 - val_mse: 0.0374
Epoch 79/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0279 - mse: 0.0279
3000/3021 [============================>.] - ETA: 0s - loss: 0.0331 - mse: 0.0331
3021/3021 [==============================] - 1s 169us/sample - loss: 0.0331 - mse: 0.0331 - val_loss: 0.0382 - val_mse: 0.0382
Epoch 80/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0339 - mse: 0.0339
2800/3021 [==========================>...] - ETA: 0s - loss: 0.0350 - mse: 0.0350
3021/3021 [==============================] - 1s 172us/sample - loss: 0.0346 - mse: 0.0346 - val_loss: 0.0368 - val_mse: 0.0368
Epoch 81/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0272 - mse: 0.0272
3021/3021 [==============================] - 0s 157us/sample - loss: 0.0326 - mse: 0.0326 - val_loss: 0.0346 - val_mse: 0.0346
Epoch 82/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0290 - mse: 0.0290
3021/3021 [==============================] - 0s 154us/sample - loss: 0.0307 - mse: 0.0307 - val_loss: 0.0363 - val_mse: 0.0363
Epoch 83/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0323 - mse: 0.0323
3021/3021 [==============================] - 0s 150us/sample - loss: 0.0313 - mse: 0.0313 - val_loss: 0.0377 - val_mse: 0.0377
Epoch 84/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0372 - mse: 0.0372
3021/3021 [==============================] - 0s 150us/sample - loss: 0.0311 - mse: 0.0311 - val_loss: 0.0336 - val_mse: 0.0336
Epoch 85/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0329 - mse: 0.0329
3000/3021 [============================>.] - ETA: 0s - loss: 0.0303 - mse: 0.0303
3021/3021 [==============================] - 0s 146us/sample - loss: 0.0302 - mse: 0.0302 - val_loss: 0.0360 - val_mse: 0.0360
Epoch 86/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0299 - mse: 0.0299
3021/3021 [==============================] - 0s 149us/sample - loss: 0.0335 - mse: 0.0335 - val_loss: 0.0364 - val_mse: 0.0364
Epoch 87/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0364 - mse: 0.0364
3000/3021 [============================>.] - ETA: 0s - loss: 0.0313 - mse: 0.0313
3021/3021 [==============================] - 1s 180us/sample - loss: 0.0313 - mse: 0.0313 - val_loss: 0.0385 - val_mse: 0.0385
Epoch 88/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0378 - mse: 0.0378
3000/3021 [============================>.] - ETA: 0s - loss: 0.0332 - mse: 0.0332
3021/3021 [==============================] - 0s 162us/sample - loss: 0.0332 - mse: 0.0332 - val_loss: 0.0366 - val_mse: 0.0366
Epoch 89/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0285 - mse: 0.0285
3021/3021 [==============================] - 0s 144us/sample - loss: 0.0345 - mse: 0.0345 - val_loss: 0.0332 - val_mse: 0.0332
Epoch 90/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0311 - mse: 0.0311
3021/3021 [==============================] - 0s 142us/sample - loss: 0.0337 - mse: 0.0337 - val_loss: 0.0778 - val_mse: 0.0778
Epoch 91/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0804 - mse: 0.0804
3021/3021 [==============================] - 0s 140us/sample - loss: 0.0456 - mse: 0.0456 - val_loss: 0.0370 - val_mse: 0.0370
Epoch 92/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0279 - mse: 0.0279
2600/3021 [========================>.....] - ETA: 0s - loss: 0.0323 - mse: 0.0323
3021/3021 [==============================] - 0s 153us/sample - loss: 0.0324 - mse: 0.0324 - val_loss: 0.0435 - val_mse: 0.0435
Epoch 93/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0395 - mse: 0.0395
3021/3021 [==============================] - 0s 145us/sample - loss: 0.0369 - mse: 0.0369 - val_loss: 0.0455 - val_mse: 0.0455
Epoch 94/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0393 - mse: 0.0393
3021/3021 [==============================] - 0s 139us/sample - loss: 0.0412 - mse: 0.0412 - val_loss: 0.0348 - val_mse: 0.0348
Epoch 95/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0374 - mse: 0.0374
3021/3021 [==============================] - 0s 153us/sample - loss: 0.0370 - mse: 0.0370 - val_loss: 0.0325 - val_mse: 0.0325
Epoch 96/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0368 - mse: 0.0368
3021/3021 [==============================] - 0s 143us/sample - loss: 0.0312 - mse: 0.0312 - val_loss: 0.0301 - val_mse: 0.0301
Epoch 97/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0267 - mse: 0.0267
3021/3021 [==============================] - 0s 154us/sample - loss: 0.0298 - mse: 0.0298 - val_loss: 0.0313 - val_mse: 0.0313
Epoch 98/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0281 - mse: 0.0281
3000/3021 [============================>.] - ETA: 0s - loss: 0.0299 - mse: 0.0299
3021/3021 [==============================] - 1s 180us/sample - loss: 0.0299 - mse: 0.0299 - val_loss: 0.0361 - val_mse: 0.0361
Epoch 99/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0351 - mse: 0.0351
3021/3021 [==============================] - 0s 156us/sample - loss: 0.0292 - mse: 0.0292 - val_loss: 0.0437 - val_mse: 0.0437
Epoch 100/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0383 - mse: 0.0383
3021/3021 [==============================] - 0s 137us/sample - loss: 0.0335 - mse: 0.0335 - val_loss: 0.0462 - val_mse: 0.0462Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-05-04T01-01-40Z
Training run 20/46 (flags = list(64, 392, 1e-04, 100, 30, "tanh", "sigmoid", 0.1, 0.05))
Using run directory runs/2020-05-04T01-02-30Z
> FLAGS <- flags(
+ flag_numeric("nodes1", 128),
+ flag_numeric("nodes2", 128),
+ flag_numeric("batch_size", 100),
+ flag_string("activation1" .... [TRUNCATED]
> model = keras_model_sequential()
> model %>%
+ layer_dense(units=FLAGS$nodes1, activation=FLAGS$activation1, input_shape=dim(efw_train2)[2]) %>%
+ layer_dropout(FLAGS$dropout1) %> .... [TRUNCATED]
> model %>% compile(
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ loss = 'mse',
+ metrics = c('mse')
+ )
> model %>% fit(
+ as.matrix(efw_train2), train2Label,
+ epochs=FLAGS$epochs,
+ batch_size=FLAGS$batch_size,
+ validation_data=list(as.matrix( .... [TRUNCATED]
Train on 3021 samples, validate on 334 samples
Epoch 1/30
100/3021 [..............................] - ETA: 11s - loss: 42.6080 - mse: 42.6080
1800/3021 [================>.............] - ETA: 0s - loss: 43.1898 - mse: 43.1898
3021/3021 [==============================] - 1s 337us/sample - loss: 42.7074 - mse: 42.7074 - val_loss: 42.2254 - val_mse: 42.2254
Epoch 2/30
100/3021 [..............................] - ETA: 0s - loss: 42.6802 - mse: 42.6802
2300/3021 [=====================>........] - ETA: 0s - loss: 41.6707 - mse: 41.6707
3021/3021 [==============================] - 1s 172us/sample - loss: 41.4810 - mse: 41.4810 - val_loss: 41.2243 - val_mse: 41.2243
Epoch 3/30
100/3021 [..............................] - ETA: 0s - loss: 42.1830 - mse: 42.1830
1500/3021 [=============>................] - ETA: 0s - loss: 40.8008 - mse: 40.8008
3021/3021 [==============================] - 1s 166us/sample - loss: 40.3972 - mse: 40.3972 - val_loss: 40.2765 - val_mse: 40.2765
Epoch 4/30
100/3021 [..............................] - ETA: 0s - loss: 38.8473 - mse: 38.8473
2600/3021 [========================>.....] - ETA: 0s - loss: 39.5304 - mse: 39.5304
3021/3021 [==============================] - 0s 159us/sample - loss: 39.5178 - mse: 39.5178 - val_loss: 39.3518 - val_mse: 39.3518
Epoch 5/30
100/3021 [..............................] - ETA: 0s - loss: 39.3601 - mse: 39.3601
2200/3021 [====================>.........] - ETA: 0s - loss: 38.8075 - mse: 38.8075
3021/3021 [==============================] - 0s 156us/sample - loss: 38.6324 - mse: 38.6324 - val_loss: 38.4399 - val_mse: 38.4399
Epoch 6/30
100/3021 [..............................] - ETA: 0s - loss: 38.6306 - mse: 38.6306
2600/3021 [========================>.....] - ETA: 0s - loss: 37.7041 - mse: 37.7040
3021/3021 [==============================] - 0s 153us/sample - loss: 37.6591 - mse: 37.6591 - val_loss: 37.5166 - val_mse: 37.5166
Epoch 7/30
100/3021 [..............................] - ETA: 0s - loss: 36.7886 - mse: 36.7886
2000/3021 [==================>...........] - ETA: 0s - loss: 36.9148 - mse: 36.9148
3021/3021 [==============================] - 0s 165us/sample - loss: 36.7103 - mse: 36.7103 - val_loss: 36.5897 - val_mse: 36.5897
Epoch 8/30
100/3021 [..............................] - ETA: 0s - loss: 36.1475 - mse: 36.1475
1300/3021 [===========>..................] - ETA: 0s - loss: 36.0399 - mse: 36.0399
3021/3021 [==============================] - 1s 173us/sample - loss: 35.6931 - mse: 35.6931 - val_loss: 35.6140 - val_mse: 35.6140
Epoch 9/30
100/3021 [..............................] - ETA: 0s - loss: 35.3412 - mse: 35.3412
2700/3021 [=========================>....] - ETA: 0s - loss: 34.7660 - mse: 34.7660
3021/3021 [==============================] - 0s 152us/sample - loss: 34.7120 - mse: 34.7120 - val_loss: 34.6135 - val_mse: 34.6135
Epoch 10/30
100/3021 [..............................] - ETA: 0s - loss: 34.4844 - mse: 34.4844
2100/3021 [===================>..........] - ETA: 0s - loss: 33.7985 - mse: 33.7985
3021/3021 [==============================] - 1s 185us/sample - loss: 33.6699 - mse: 33.6699 - val_loss: 33.6034 - val_mse: 33.6034
Epoch 11/30
100/3021 [..............................] - ETA: 0s - loss: 34.6944 - mse: 34.6944
2100/3021 [===================>..........] - ETA: 0s - loss: 32.9045 - mse: 32.9045
3021/3021 [==============================] - 1s 184us/sample - loss: 32.6789 - mse: 32.6789 - val_loss: 32.5589 - val_mse: 32.5589
Epoch 12/30
100/3021 [..............................] - ETA: 0s - loss: 33.0288 - mse: 33.0288
1700/3021 [===============>..............] - ETA: 0s - loss: 32.0491 - mse: 32.0491
3021/3021 [==============================] - 1s 169us/sample - loss: 31.6149 - mse: 31.6149 - val_loss: 31.5208 - val_mse: 31.5208
Epoch 13/30
100/3021 [..............................] - ETA: 0s - loss: 30.7211 - mse: 30.7211
1800/3021 [================>.............] - ETA: 0s - loss: 30.7009 - mse: 30.7009
3021/3021 [==============================] - 1s 184us/sample - loss: 30.4914 - mse: 30.4914 - val_loss: 30.4347 - val_mse: 30.4347
Epoch 14/30
100/3021 [..............................] - ETA: 0s - loss: 30.2156 - mse: 30.2156
1800/3021 [================>.............] - ETA: 0s - loss: 29.7016 - mse: 29.7016
3021/3021 [==============================] - 0s 162us/sample - loss: 29.4785 - mse: 29.4785 - val_loss: 29.3560 - val_mse: 29.3560
Epoch 15/30
100/3021 [..............................] - ETA: 0s - loss: 28.5063 - mse: 28.5063
2700/3021 [=========================>....] - ETA: 0s - loss: 28.3949 - mse: 28.3949
3021/3021 [==============================] - 0s 151us/sample - loss: 28.3356 - mse: 28.3356 - val_loss: 28.2490 - val_mse: 28.2490
Epoch 16/30
100/3021 [..............................] - ETA: 0s - loss: 28.0878 - mse: 28.0878
2600/3021 [========================>.....] - ETA: 0s - loss: 27.3139 - mse: 27.3139
3021/3021 [==============================] - 0s 149us/sample - loss: 27.2236 - mse: 27.2236 - val_loss: 27.1466 - val_mse: 27.1466
Epoch 17/30
100/3021 [..............................] - ETA: 0s - loss: 26.5906 - mse: 26.5906
2400/3021 [======================>.......] - ETA: 0s - loss: 26.1624 - mse: 26.1624
3021/3021 [==============================] - 0s 153us/sample - loss: 26.0969 - mse: 26.0969 - val_loss: 26.0261 - val_mse: 26.0261
Epoch 18/30
100/3021 [..............................] - ETA: 0s - loss: 25.7960 - mse: 25.7960
1600/3021 [==============>...............] - ETA: 0s - loss: 25.2550 - mse: 25.2550
3021/3021 [==============================] - 0s 151us/sample - loss: 24.9392 - mse: 24.9392 - val_loss: 24.8751 - val_mse: 24.8751
Epoch 19/30
100/3021 [..............................] - ETA: 0s - loss: 24.8684 - mse: 24.8684
1700/3021 [===============>..............] - ETA: 0s - loss: 24.0699 - mse: 24.0699
3021/3021 [==============================] - 0s 155us/sample - loss: 23.7936 - mse: 23.7936 - val_loss: 23.7488 - val_mse: 23.7488
Epoch 20/30
100/3021 [..............................] - ETA: 0s - loss: 22.0818 - mse: 22.0818
1800/3021 [================>.............] - ETA: 0s - loss: 22.8616 - mse: 22.8616
3021/3021 [==============================] - 0s 151us/sample - loss: 22.5930 - mse: 22.5930 - val_loss: 22.6364 - val_mse: 22.6364
Epoch 21/30
100/3021 [..............................] - ETA: 0s - loss: 21.6634 - mse: 21.6634
2300/3021 [=====================>........] - ETA: 0s - loss: 21.6380 - mse: 21.6380
3021/3021 [==============================] - 0s 150us/sample - loss: 21.5715 - mse: 21.5715 - val_loss: 21.5045 - val_mse: 21.5045
Epoch 22/30
100/3021 [..............................] - ETA: 0s - loss: 21.2448 - mse: 21.2448
2500/3021 [=======================>......] - ETA: 0s - loss: 20.3726 - mse: 20.3726
3021/3021 [==============================] - 0s 150us/sample - loss: 20.3130 - mse: 20.3130 - val_loss: 20.3927 - val_mse: 20.3927
Epoch 23/30
100/3021 [..............................] - ETA: 0s - loss: 20.1187 - mse: 20.1187
1700/3021 [===============>..............] - ETA: 0s - loss: 19.5178 - mse: 19.5178
3021/3021 [==============================] - 1s 166us/sample - loss: 19.3653 - mse: 19.3653 - val_loss: 19.3009 - val_mse: 19.3009
Epoch 24/30
100/3021 [..............................] - ETA: 0s - loss: 19.3037 - mse: 19.3037
2500/3021 [=======================>......] - ETA: 0s - loss: 18.4149 - mse: 18.4149
3021/3021 [==============================] - 0s 152us/sample - loss: 18.2366 - mse: 18.2366 - val_loss: 18.1831 - val_mse: 18.1831
Epoch 25/30
100/3021 [..............................] - ETA: 0s - loss: 17.3298 - mse: 17.3298
2700/3021 [=========================>....] - ETA: 0s - loss: 17.2294 - mse: 17.2294
3021/3021 [==============================] - 0s 146us/sample - loss: 17.2205 - mse: 17.2205 - val_loss: 17.1056 - val_mse: 17.1056
Epoch 26/30
100/3021 [..............................] - ETA: 0s - loss: 15.8818 - mse: 15.8818
1900/3021 [=================>............] - ETA: 0s - loss: 16.1339 - mse: 16.1339
3021/3021 [==============================] - 0s 149us/sample - loss: 16.0184 - mse: 16.0184 - val_loss: 16.0481 - val_mse: 16.0481
Epoch 27/30
100/3021 [..............................] - ETA: 0s - loss: 15.7404 - mse: 15.7404
2600/3021 [========================>.....] - ETA: 0s - loss: 15.0362 - mse: 15.0362
3021/3021 [==============================] - 0s 145us/sample - loss: 15.0247 - mse: 15.0247 - val_loss: 15.0412 - val_mse: 15.0412
Epoch 28/30
100/3021 [..............................] - ETA: 0s - loss: 14.6841 - mse: 14.6841
2100/3021 [===================>..........] - ETA: 0s - loss: 14.2838 - mse: 14.2838
3021/3021 [==============================] - 0s 164us/sample - loss: 14.0781 - mse: 14.0781 - val_loss: 14.0520 - val_mse: 14.0520
Epoch 29/30
100/3021 [..............................] - ETA: 0s - loss: 13.3978 - mse: 13.3978
1900/3021 [=================>............] - ETA: 0s - loss: 13.1456 - mse: 13.1456
3021/3021 [==============================] - 0s 158us/sample - loss: 13.0020 - mse: 13.0020 - val_loss: 13.1031 - val_mse: 13.1031
Epoch 30/30
100/3021 [..............................] - ETA: 0s - loss: 13.3412 - mse: 13.3412
2800/3021 [==========================>...] - ETA: 0s - loss: 12.1751 - mse: 12.1751
3021/3021 [==============================] - 0s 147us/sample - loss: 12.1399 - mse: 12.1399 - val_loss: 12.1625 - val_mse: 12.1625Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-05-04T01-02-30Z
Training run 21/46 (flags = list(392, 128, 1e-04, 200, 30, "relu", "tanh", 0.05, 0.2))
Using run directory runs/2020-05-04T01-02-49Z
> FLAGS <- flags(
+ flag_numeric("nodes1", 128),
+ flag_numeric("nodes2", 128),
+ flag_numeric("batch_size", 100),
+ flag_string("activation1" .... [TRUNCATED]
> model = keras_model_sequential()
> model %>%
+ layer_dense(units=FLAGS$nodes1, activation=FLAGS$activation1, input_shape=dim(efw_train2)[2]) %>%
+ layer_dropout(FLAGS$dropout1) %> .... [TRUNCATED]
> model %>% compile(
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ loss = 'mse',
+ metrics = c('mse')
+ )
> model %>% fit(
+ as.matrix(efw_train2), train2Label,
+ epochs=FLAGS$epochs,
+ batch_size=FLAGS$batch_size,
+ validation_data=list(as.matrix( .... [TRUNCATED]
Train on 3021 samples, validate on 334 samples
Epoch 1/30
200/3021 [>.............................] - ETA: 3s - loss: 40.7380 - mse: 40.7380
2600/3021 [========================>.....] - ETA: 0s - loss: 40.7601 - mse: 40.7601
3021/3021 [==============================] - 1s 261us/sample - loss: 40.5561 - mse: 40.5561 - val_loss: 38.9674 - val_mse: 38.9674
Epoch 2/30
200/3021 [>.............................] - ETA: 0s - loss: 38.4097 - mse: 38.4097
2600/3021 [========================>.....] - ETA: 0s - loss: 37.6203 - mse: 37.6203
3021/3021 [==============================] - 0s 158us/sample - loss: 37.5074 - mse: 37.5074 - val_loss: 36.0521 - val_mse: 36.0521
Epoch 3/30
200/3021 [>.............................] - ETA: 0s - loss: 36.3504 - mse: 36.3504
2600/3021 [========================>.....] - ETA: 0s - loss: 34.8498 - mse: 34.8498
3021/3021 [==============================] - 0s 163us/sample - loss: 34.7103 - mse: 34.7103 - val_loss: 33.3020 - val_mse: 33.3020
Epoch 4/30
200/3021 [>.............................] - ETA: 0s - loss: 33.3087 - mse: 33.3087
2200/3021 [====================>.........] - ETA: 0s - loss: 32.5592 - mse: 32.5592
3021/3021 [==============================] - 0s 156us/sample - loss: 32.0263 - mse: 32.0263 - val_loss: 30.7105 - val_mse: 30.7105
Epoch 5/30
200/3021 [>.............................] - ETA: 0s - loss: 29.2788 - mse: 29.2788
2400/3021 [======================>.......] - ETA: 0s - loss: 29.5917 - mse: 29.5917
3021/3021 [==============================] - 0s 157us/sample - loss: 29.4919 - mse: 29.4919 - val_loss: 28.2602 - val_mse: 28.2602
Epoch 6/30
200/3021 [>.............................] - ETA: 0s - loss: 28.0507 - mse: 28.0507
2600/3021 [========================>.....] - ETA: 0s - loss: 27.1526 - mse: 27.1526
3021/3021 [==============================] - 0s 157us/sample - loss: 27.0964 - mse: 27.0964 - val_loss: 25.9285 - val_mse: 25.9285
Epoch 7/30
200/3021 [>.............................] - ETA: 0s - loss: 25.7852 - mse: 25.7852
2200/3021 [====================>.........] - ETA: 0s - loss: 25.1679 - mse: 25.1679
3021/3021 [==============================] - 1s 172us/sample - loss: 24.8840 - mse: 24.8840 - val_loss: 23.7625 - val_mse: 23.7625
Epoch 8/30
200/3021 [>.............................] - ETA: 0s - loss: 21.5420 - mse: 21.5420
2400/3021 [======================>.......] - ETA: 0s - loss: 22.9323 - mse: 22.9323
3021/3021 [==============================] - 0s 160us/sample - loss: 22.7788 - mse: 22.7788 - val_loss: 21.7443 - val_mse: 21.7443
Epoch 9/30
200/3021 [>.............................] - ETA: 0s - loss: 20.8936 - mse: 20.8936
2000/3021 [==================>...........] - ETA: 0s - loss: 21.1934 - mse: 21.1934
3021/3021 [==============================] - 0s 161us/sample - loss: 20.8732 - mse: 20.8732 - val_loss: 19.9021 - val_mse: 19.9021
Epoch 10/30
200/3021 [>.............................] - ETA: 0s - loss: 20.0728 - mse: 20.0728
2200/3021 [====================>.........] - ETA: 0s - loss: 19.3088 - mse: 19.3088
3021/3021 [==============================] - 0s 151us/sample - loss: 19.0898 - mse: 19.0898 - val_loss: 18.2233 - val_mse: 18.2233
Epoch 11/30
200/3021 [>.............................] - ETA: 0s - loss: 17.8324 - mse: 17.8324
2200/3021 [====================>.........] - ETA: 0s - loss: 17.7380 - mse: 17.7380
3021/3021 [==============================] - 0s 158us/sample - loss: 17.5288 - mse: 17.5288 - val_loss: 16.7084 - val_mse: 16.7084
Epoch 12/30
200/3021 [>.............................] - ETA: 0s - loss: 16.6235 - mse: 16.6235
2400/3021 [======================>.......] - ETA: 0s - loss: 16.2724 - mse: 16.2724
3021/3021 [==============================] - 0s 155us/sample - loss: 16.0842 - mse: 16.0842 - val_loss: 15.3697 - val_mse: 15.3697
Epoch 13/30
200/3021 [>.............................] - ETA: 0s - loss: 15.1332 - mse: 15.1332
2800/3021 [==========================>...] - ETA: 0s - loss: 14.8754 - mse: 14.8754
3021/3021 [==============================] - 0s 152us/sample - loss: 14.8534 - mse: 14.8534 - val_loss: 14.1791 - val_mse: 14.1791
Epoch 14/30
200/3021 [>.............................] - ETA: 0s - loss: 13.5926 - mse: 13.5926
2600/3021 [========================>.....] - ETA: 0s - loss: 13.6548 - mse: 13.6548
3021/3021 [==============================] - 0s 163us/sample - loss: 13.6948 - mse: 13.6948 - val_loss: 13.1169 - val_mse: 13.1169
Epoch 15/30
200/3021 [>.............................] - ETA: 0s - loss: 13.2934 - mse: 13.2934
2400/3021 [======================>.......] - ETA: 0s - loss: 12.9500 - mse: 12.9500
3021/3021 [==============================] - 0s 159us/sample - loss: 12.7059 - mse: 12.7059 - val_loss: 12.1764 - val_mse: 12.1764
Epoch 16/30
200/3021 [>.............................] - ETA: 0s - loss: 13.3039 - mse: 13.3039
2600/3021 [========================>.....] - ETA: 0s - loss: 11.8684 - mse: 11.8684
3021/3021 [==============================] - 1s 180us/sample - loss: 11.8330 - mse: 11.8330 - val_loss: 11.3535 - val_mse: 11.3535
Epoch 17/30
200/3021 [>.............................] - ETA: 0s - loss: 11.7812 - mse: 11.7812
2600/3021 [========================>.....] - ETA: 0s - loss: 11.1551 - mse: 11.1551
3021/3021 [==============================] - 1s 169us/sample - loss: 11.0796 - mse: 11.0796 - val_loss: 10.6137 - val_mse: 10.6137
Epoch 18/30
200/3021 [>.............................] - ETA: 0s - loss: 11.1018 - mse: 11.1018
2400/3021 [======================>.......] - ETA: 0s - loss: 10.5176 - mse: 10.5176
3021/3021 [==============================] - 0s 163us/sample - loss: 10.3838 - mse: 10.3838 - val_loss: 9.9599 - val_mse: 9.9599
Epoch 19/30
200/3021 [>.............................] - ETA: 0s - loss: 10.4826 - mse: 10.4826
1800/3021 [================>.............] - ETA: 0s - loss: 9.8806 - mse: 9.8806
3021/3021 [==============================] - 0s 161us/sample - loss: 9.7733 - mse: 9.7733 - val_loss: 9.3771 - val_mse: 9.3771
Epoch 20/30
200/3021 [>.............................] - ETA: 0s - loss: 9.6836 - mse: 9.6836
1800/3021 [================>.............] - ETA: 0s - loss: 9.2342 - mse: 9.2342
3021/3021 [==============================] - 0s 153us/sample - loss: 9.1995 - mse: 9.1995 - val_loss: 8.8497 - val_mse: 8.8497
Epoch 21/30
200/3021 [>.............................] - ETA: 0s - loss: 9.4219 - mse: 9.4219
2600/3021 [========================>.....] - ETA: 0s - loss: 8.7563 - mse: 8.7563
3021/3021 [==============================] - 0s 149us/sample - loss: 8.7122 - mse: 8.7122 - val_loss: 8.3630 - val_mse: 8.3630
Epoch 22/30
200/3021 [>.............................] - ETA: 0s - loss: 9.1641 - mse: 9.1641
2200/3021 [====================>.........] - ETA: 0s - loss: 8.3413 - mse: 8.3413
3021/3021 [==============================] - 0s 163us/sample - loss: 8.2523 - mse: 8.2523 - val_loss: 7.9120 - val_mse: 7.9120
Epoch 23/30
200/3021 [>.............................] - ETA: 0s - loss: 7.6146 - mse: 7.6146
2000/3021 [==================>...........] - ETA: 0s - loss: 7.9053 - mse: 7.9053
3021/3021 [==============================] - 0s 158us/sample - loss: 7.8138 - mse: 7.8138 - val_loss: 7.4919 - val_mse: 7.4919
Epoch 24/30
200/3021 [>.............................] - ETA: 0s - loss: 7.3986 - mse: 7.3986
2600/3021 [========================>.....] - ETA: 0s - loss: 7.4928 - mse: 7.4928
3021/3021 [==============================] - 0s 161us/sample - loss: 7.4080 - mse: 7.4080 - val_loss: 7.1062 - val_mse: 7.1062
Epoch 25/30
200/3021 [>.............................] - ETA: 0s - loss: 7.3604 - mse: 7.3604
2000/3021 [==================>...........] - ETA: 0s - loss: 6.9522 - mse: 6.9522
3021/3021 [==============================] - 0s 156us/sample - loss: 7.0296 - mse: 7.0296 - val_loss: 6.7444 - val_mse: 6.7444
Epoch 26/30
200/3021 [>.............................] - ETA: 0s - loss: 7.8383 - mse: 7.8383
2600/3021 [========================>.....] - ETA: 0s - loss: 6.6751 - mse: 6.6751
3021/3021 [==============================] - 0s 155us/sample - loss: 6.6855 - mse: 6.6855 - val_loss: 6.4013 - val_mse: 6.4013
Epoch 27/30
200/3021 [>.............................] - ETA: 0s - loss: 7.0182 - mse: 7.0182
2000/3021 [==================>...........] - ETA: 0s - loss: 6.4738 - mse: 6.4738
3021/3021 [==============================] - 0s 156us/sample - loss: 6.3423 - mse: 6.3423 - val_loss: 6.0749 - val_mse: 6.0749
Epoch 28/30
200/3021 [>.............................] - ETA: 0s - loss: 5.6900 - mse: 5.6900
2400/3021 [======================>.......] - ETA: 0s - loss: 5.9304 - mse: 5.9304
3021/3021 [==============================] - 1s 166us/sample - loss: 6.0132 - mse: 6.0132 - val_loss: 5.7599 - val_mse: 5.7599
Epoch 29/30
200/3021 [>.............................] - ETA: 0s - loss: 6.3917 - mse: 6.3917
2400/3021 [======================>.......] - ETA: 0s - loss: 5.7090 - mse: 5.7090
3021/3021 [==============================] - 0s 159us/sample - loss: 5.7222 - mse: 5.7222 - val_loss: 5.4685 - val_mse: 5.4685
Epoch 30/30
200/3021 [>.............................] - ETA: 0s - loss: 5.4854 - mse: 5.4854
2800/3021 [==========================>...] - ETA: 0s - loss: 5.4435 - mse: 5.4435
3021/3021 [==============================] - 1s 166us/sample - loss: 5.4255 - mse: 5.4255 - val_loss: 5.1874 - val_mse: 5.1874Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-05-04T01-02-49Z
Training run 22/46 (flags = list(64, 64, 0.05, 200, 50, "relu", "tanh", 0.5, 0.2))
Using run directory runs/2020-05-04T01-03-07Z
> FLAGS <- flags(
+ flag_numeric("nodes1", 128),
+ flag_numeric("nodes2", 128),
+ flag_numeric("batch_size", 100),
+ flag_string("activation1" .... [TRUNCATED]
> model = keras_model_sequential()
> model %>%
+ layer_dense(units=FLAGS$nodes1, activation=FLAGS$activation1, input_shape=dim(efw_train2)[2]) %>%
+ layer_dropout(FLAGS$dropout1) %> .... [TRUNCATED]
> model %>% compile(
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ loss = 'mse',
+ metrics = c('mse')
+ )
> model %>% fit(
+ as.matrix(efw_train2), train2Label,
+ epochs=FLAGS$epochs,
+ batch_size=FLAGS$batch_size,
+ validation_data=list(as.matrix( .... [TRUNCATED]
Train on 3021 samples, validate on 334 samples
Epoch 1/50
200/3021 [>.............................] - ETA: 3s - loss: 44.4298 - mse: 44.4298
3021/3021 [==============================] - 1s 243us/sample - loss: 10.9978 - mse: 10.9978 - val_loss: 1.5470 - val_mse: 1.5470
Epoch 2/50
200/3021 [>.............................] - ETA: 0s - loss: 3.3841 - mse: 3.3841
3021/3021 [==============================] - 0s 146us/sample - loss: 2.8072 - mse: 2.8072 - val_loss: 0.7576 - val_mse: 0.7576
Epoch 3/50
200/3021 [>.............................] - ETA: 0s - loss: 2.1010 - mse: 2.1010
3021/3021 [==============================] - 0s 150us/sample - loss: 1.8852 - mse: 1.8852 - val_loss: 0.5126 - val_mse: 0.5126
Epoch 4/50
200/3021 [>.............................] - ETA: 0s - loss: 1.7017 - mse: 1.7017
3021/3021 [==============================] - 0s 146us/sample - loss: 1.5865 - mse: 1.5865 - val_loss: 0.3950 - val_mse: 0.3950
Epoch 5/50
200/3021 [>.............................] - ETA: 0s - loss: 1.6524 - mse: 1.6524
2600/3021 [========================>.....] - ETA: 0s - loss: 1.3663 - mse: 1.3663
3021/3021 [==============================] - 0s 153us/sample - loss: 1.3442 - mse: 1.3442 - val_loss: 0.3186 - val_mse: 0.3186
Epoch 6/50
200/3021 [>.............................] - ETA: 0s - loss: 1.1127 - mse: 1.1127
3021/3021 [==============================] - 0s 142us/sample - loss: 1.1509 - mse: 1.1509 - val_loss: 0.2150 - val_mse: 0.2150
Epoch 7/50
200/3021 [>.............................] - ETA: 0s - loss: 1.0250 - mse: 1.0250
2600/3021 [========================>.....] - ETA: 0s - loss: 1.0787 - mse: 1.0787
3021/3021 [==============================] - 0s 147us/sample - loss: 1.0659 - mse: 1.0659 - val_loss: 0.3580 - val_mse: 0.3580
Epoch 8/50
200/3021 [>.............................] - ETA: 0s - loss: 1.0123 - mse: 1.0123
3021/3021 [==============================] - 0s 145us/sample - loss: 0.9576 - mse: 0.9576 - val_loss: 0.1925 - val_mse: 0.1925
Epoch 9/50
200/3021 [>.............................] - ETA: 0s - loss: 0.9682 - mse: 0.9682
3021/3021 [==============================] - 0s 145us/sample - loss: 0.9195 - mse: 0.9195 - val_loss: 0.2822 - val_mse: 0.2822
Epoch 10/50
200/3021 [>.............................] - ETA: 0s - loss: 0.9470 - mse: 0.9470
3021/3021 [==============================] - 0s 143us/sample - loss: 0.9056 - mse: 0.9056 - val_loss: 0.2604 - val_mse: 0.2604
Epoch 11/50
200/3021 [>.............................] - ETA: 0s - loss: 0.6961 - mse: 0.6961
3021/3021 [==============================] - 0s 153us/sample - loss: 0.7294 - mse: 0.7294 - val_loss: 0.1228 - val_mse: 0.1228
Epoch 12/50
200/3021 [>.............................] - ETA: 0s - loss: 0.6699 - mse: 0.6699
3021/3021 [==============================] - 0s 155us/sample - loss: 0.6331 - mse: 0.6331 - val_loss: 0.1324 - val_mse: 0.1324
Epoch 13/50
200/3021 [>.............................] - ETA: 0s - loss: 0.5661 - mse: 0.5661
3021/3021 [==============================] - 0s 143us/sample - loss: 0.6102 - mse: 0.6102 - val_loss: 0.1053 - val_mse: 0.1053
Epoch 14/50
200/3021 [>.............................] - ETA: 0s - loss: 0.4635 - mse: 0.4635
3021/3021 [==============================] - 0s 146us/sample - loss: 0.5794 - mse: 0.5794 - val_loss: 0.2546 - val_mse: 0.2546
Epoch 15/50
200/3021 [>.............................] - ETA: 0s - loss: 0.7525 - mse: 0.7525
3021/3021 [==============================] - 0s 147us/sample - loss: 0.5783 - mse: 0.5783 - val_loss: 0.1407 - val_mse: 0.1407
Epoch 16/50
200/3021 [>.............................] - ETA: 0s - loss: 0.4649 - mse: 0.4649
3000/3021 [============================>.] - ETA: 0s - loss: 0.4877 - mse: 0.4877
3021/3021 [==============================] - 0s 144us/sample - loss: 0.4870 - mse: 0.4870 - val_loss: 0.0918 - val_mse: 0.0918
Epoch 17/50
200/3021 [>.............................] - ETA: 0s - loss: 0.4271 - mse: 0.4271
3021/3021 [==============================] - 0s 146us/sample - loss: 0.4533 - mse: 0.4533 - val_loss: 0.1092 - val_mse: 0.1092
Epoch 18/50
200/3021 [>.............................] - ETA: 0s - loss: 0.4863 - mse: 0.4863
3021/3021 [==============================] - 0s 143us/sample - loss: 0.4235 - mse: 0.4235 - val_loss: 0.1364 - val_mse: 0.1364
Epoch 19/50
200/3021 [>.............................] - ETA: 0s - loss: 0.3904 - mse: 0.3904
3021/3021 [==============================] - 0s 154us/sample - loss: 0.3820 - mse: 0.3820 - val_loss: 0.0746 - val_mse: 0.0746
Epoch 20/50
200/3021 [>.............................] - ETA: 0s - loss: 0.3225 - mse: 0.3225
2600/3021 [========================>.....] - ETA: 0s - loss: 0.3474 - mse: 0.3474
3021/3021 [==============================] - 0s 151us/sample - loss: 0.3436 - mse: 0.3436 - val_loss: 0.1363 - val_mse: 0.1363
Epoch 21/50
200/3021 [>.............................] - ETA: 0s - loss: 0.3818 - mse: 0.3818
3021/3021 [==============================] - 0s 141us/sample - loss: 0.3515 - mse: 0.3515 - val_loss: 0.1985 - val_mse: 0.1985
Epoch 22/50
200/3021 [>.............................] - ETA: 0s - loss: 0.4506 - mse: 0.4506
3021/3021 [==============================] - 0s 142us/sample - loss: 0.3592 - mse: 0.3592 - val_loss: 0.0671 - val_mse: 0.0671
Epoch 23/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2342 - mse: 0.2342
3021/3021 [==============================] - 0s 143us/sample - loss: 0.2895 - mse: 0.2895 - val_loss: 0.0998 - val_mse: 0.0998
Epoch 24/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2685 - mse: 0.2685
3021/3021 [==============================] - 0s 141us/sample - loss: 0.3176 - mse: 0.3176 - val_loss: 0.0989 - val_mse: 0.0989
Epoch 25/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2345 - mse: 0.2345
2800/3021 [==========================>...] - ETA: 0s - loss: 0.2739 - mse: 0.2739
3021/3021 [==============================] - 0s 154us/sample - loss: 0.2747 - mse: 0.2747 - val_loss: 0.2120 - val_mse: 0.2120
Epoch 26/50
200/3021 [>.............................] - ETA: 0s - loss: 0.3565 - mse: 0.3565
3021/3021 [==============================] - 0s 146us/sample - loss: 0.3474 - mse: 0.3474 - val_loss: 0.1961 - val_mse: 0.1961
Epoch 27/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2874 - mse: 0.2874
3021/3021 [==============================] - 0s 138us/sample - loss: 0.2737 - mse: 0.2737 - val_loss: 0.1056 - val_mse: 0.1056
Epoch 28/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2247 - mse: 0.2247
3021/3021 [==============================] - 0s 150us/sample - loss: 0.2233 - mse: 0.2233 - val_loss: 0.0863 - val_mse: 0.0863
Epoch 29/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2417 - mse: 0.2417
3021/3021 [==============================] - 0s 141us/sample - loss: 0.2240 - mse: 0.2240 - val_loss: 0.1263 - val_mse: 0.1263
Epoch 30/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2245 - mse: 0.2245
3021/3021 [==============================] - 0s 138us/sample - loss: 0.2337 - mse: 0.2337 - val_loss: 0.2159 - val_mse: 0.2159
Epoch 31/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2674 - mse: 0.2674
3021/3021 [==============================] - 0s 134us/sample - loss: 0.2526 - mse: 0.2526 - val_loss: 0.0901 - val_mse: 0.0901
Epoch 32/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2474 - mse: 0.2474
2800/3021 [==========================>...] - ETA: 0s - loss: 0.2371 - mse: 0.2371
3021/3021 [==============================] - 0s 141us/sample - loss: 0.2334 - mse: 0.2334 - val_loss: 0.0885 - val_mse: 0.0885
Epoch 33/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2312 - mse: 0.2312
3021/3021 [==============================] - 1s 173us/sample - loss: 0.2105 - mse: 0.2105 - val_loss: 0.1704 - val_mse: 0.1704
Epoch 34/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2788 - mse: 0.2788
3000/3021 [============================>.] - ETA: 0s - loss: 0.2148 - mse: 0.2148
3021/3021 [==============================] - 0s 161us/sample - loss: 0.2147 - mse: 0.2147 - val_loss: 0.1075 - val_mse: 0.1075
Epoch 35/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2036 - mse: 0.2036
3021/3021 [==============================] - 0s 153us/sample - loss: 0.2093 - mse: 0.2093 - val_loss: 0.1206 - val_mse: 0.1206
Epoch 36/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2159 - mse: 0.2159
3021/3021 [==============================] - 0s 146us/sample - loss: 0.2429 - mse: 0.2429 - val_loss: 0.1023 - val_mse: 0.1023
Epoch 37/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2032 - mse: 0.2032
3021/3021 [==============================] - 0s 155us/sample - loss: 0.2298 - mse: 0.2298 - val_loss: 0.1024 - val_mse: 0.1024
Epoch 38/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1903 - mse: 0.1903
3021/3021 [==============================] - 0s 133us/sample - loss: 0.2041 - mse: 0.2041 - val_loss: 0.1355 - val_mse: 0.1355
Epoch 39/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2149 - mse: 0.2149
3021/3021 [==============================] - 0s 161us/sample - loss: 0.2079 - mse: 0.2079 - val_loss: 0.1476 - val_mse: 0.1476
Epoch 40/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2413 - mse: 0.2413
3021/3021 [==============================] - 0s 143us/sample - loss: 0.2335 - mse: 0.2335 - val_loss: 0.1932 - val_mse: 0.1932
Epoch 41/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2476 - mse: 0.2476
3021/3021 [==============================] - 0s 144us/sample - loss: 0.2110 - mse: 0.2110 - val_loss: 0.1508 - val_mse: 0.1508
Epoch 42/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2536 - mse: 0.2536
3021/3021 [==============================] - 0s 138us/sample - loss: 0.2081 - mse: 0.2081 - val_loss: 0.1101 - val_mse: 0.1101
Epoch 43/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1985 - mse: 0.1985
3021/3021 [==============================] - 0s 141us/sample - loss: 0.1885 - mse: 0.1885 - val_loss: 0.2362 - val_mse: 0.2362
Epoch 44/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2942 - mse: 0.2942
3021/3021 [==============================] - 0s 146us/sample - loss: 0.2211 - mse: 0.2211 - val_loss: 0.1023 - val_mse: 0.1023
Epoch 45/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1752 - mse: 0.1752
2000/3021 [==================>...........] - ETA: 0s - loss: 0.1960 - mse: 0.1960
3021/3021 [==============================] - 0s 154us/sample - loss: 0.1932 - mse: 0.1932 - val_loss: 0.1040 - val_mse: 0.1040
Epoch 46/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1480 - mse: 0.1480
3021/3021 [==============================] - 0s 135us/sample - loss: 0.1948 - mse: 0.1948 - val_loss: 0.1356 - val_mse: 0.1356
Epoch 47/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2191 - mse: 0.2191
3021/3021 [==============================] - 0s 134us/sample - loss: 0.1922 - mse: 0.1922 - val_loss: 0.1214 - val_mse: 0.1214
Epoch 48/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1934 - mse: 0.1934
3021/3021 [==============================] - 0s 145us/sample - loss: 0.2033 - mse: 0.2033 - val_loss: 0.1230 - val_mse: 0.1230
Epoch 49/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2193 - mse: 0.2193
3021/3021 [==============================] - 0s 149us/sample - loss: 0.2042 - mse: 0.2042 - val_loss: 0.1075 - val_mse: 0.1075
Epoch 50/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2595 - mse: 0.2595
3021/3021 [==============================] - 0s 139us/sample - loss: 0.2077 - mse: 0.2077 - val_loss: 0.1075 - val_mse: 0.1075Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-05-04T01-03-07Z
Training run 23/46 (flags = list(128, 392, 0.001, 100, 100, "relu", "relu", 0.5, 0.2))
Using run directory runs/2020-05-04T01-03-33Z
> FLAGS <- flags(
+ flag_numeric("nodes1", 128),
+ flag_numeric("nodes2", 128),
+ flag_numeric("batch_size", 100),
+ flag_string("activation1" .... [TRUNCATED]
> model = keras_model_sequential()
> model %>%
+ layer_dense(units=FLAGS$nodes1, activation=FLAGS$activation1, input_shape=dim(efw_train2)[2]) %>%
+ layer_dropout(FLAGS$dropout1) %> .... [TRUNCATED]
> model %>% compile(
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ loss = 'mse',
+ metrics = c('mse')
+ )
> model %>% fit(
+ as.matrix(efw_train2), train2Label,
+ epochs=FLAGS$epochs,
+ batch_size=FLAGS$batch_size,
+ validation_data=list(as.matrix( .... [TRUNCATED]
Train on 3021 samples, validate on 334 samples
Epoch 1/100
100/3021 [..............................] - ETA: 7s - loss: 42.4754 - mse: 42.4754
2400/3021 [======================>.......] - ETA: 0s - loss: 33.7694 - mse: 33.7694
3021/3021 [==============================] - 1s 253us/sample - loss: 31.5105 - mse: 31.5105 - val_loss: 20.2058 - val_mse: 20.2058
Epoch 2/100
100/3021 [..............................] - ETA: 0s - loss: 20.9594 - mse: 20.9594
2200/3021 [====================>.........] - ETA: 0s - loss: 16.3854 - mse: 16.3854
3021/3021 [==============================] - 1s 169us/sample - loss: 15.2896 - mse: 15.2896 - val_loss: 10.5124 - val_mse: 10.5124
Epoch 3/100
100/3021 [..............................] - ETA: 0s - loss: 10.6211 - mse: 10.6211
1900/3021 [=================>............] - ETA: 0s - loss: 9.8299 - mse: 9.8299
3021/3021 [==============================] - 1s 166us/sample - loss: 9.4133 - mse: 9.4133 - val_loss: 6.4783 - val_mse: 6.4783
Epoch 4/100
100/3021 [..............................] - ETA: 0s - loss: 8.0059 - mse: 8.0059
1900/3021 [=================>............] - ETA: 0s - loss: 6.9506 - mse: 6.9506
3021/3021 [==============================] - 0s 160us/sample - loss: 6.4552 - mse: 6.4552 - val_loss: 4.0076 - val_mse: 4.0076
Epoch 5/100
100/3021 [..............................] - ETA: 0s - loss: 4.7177 - mse: 4.7177
2000/3021 [==================>...........] - ETA: 0s - loss: 4.7371 - mse: 4.7371
3021/3021 [==============================] - 1s 166us/sample - loss: 4.4431 - mse: 4.4431 - val_loss: 2.5202 - val_mse: 2.5202
Epoch 6/100
100/3021 [..............................] - ETA: 0s - loss: 3.2785 - mse: 3.2785
1800/3021 [================>.............] - ETA: 0s - loss: 3.3268 - mse: 3.3268
3021/3021 [==============================] - 0s 155us/sample - loss: 3.2602 - mse: 3.2602 - val_loss: 1.6484 - val_mse: 1.6484
Epoch 7/100
100/3021 [..............................] - ETA: 0s - loss: 2.5614 - mse: 2.5614
2000/3021 [==================>...........] - ETA: 0s - loss: 2.7253 - mse: 2.7253
3021/3021 [==============================] - 1s 177us/sample - loss: 2.6274 - mse: 2.6274 - val_loss: 1.1284 - val_mse: 1.1284
Epoch 8/100
100/3021 [..............................] - ETA: 0s - loss: 2.4431 - mse: 2.4431
1500/3021 [=============>................] - ETA: 0s - loss: 2.2600 - mse: 2.2600
3021/3021 [==============================] - 0s 165us/sample - loss: 2.1382 - mse: 2.1382 - val_loss: 0.7985 - val_mse: 0.7985
Epoch 9/100
100/3021 [..............................] - ETA: 0s - loss: 1.9411 - mse: 1.9411
2000/3021 [==================>...........] - ETA: 0s - loss: 1.9117 - mse: 1.9117
3021/3021 [==============================] - 1s 166us/sample - loss: 1.9350 - mse: 1.9350 - val_loss: 0.6330 - val_mse: 0.6330
Epoch 10/100
100/3021 [..............................] - ETA: 0s - loss: 1.8019 - mse: 1.8019
1200/3021 [==========>...................] - ETA: 0s - loss: 1.7675 - mse: 1.7675
3021/3021 [==============================] - 0s 159us/sample - loss: 1.6579 - mse: 1.6579 - val_loss: 0.5141 - val_mse: 0.5141
Epoch 11/100
100/3021 [..............................] - ETA: 0s - loss: 1.3896 - mse: 1.3896
2300/3021 [=====================>........] - ETA: 0s - loss: 1.6065 - mse: 1.6065
3021/3021 [==============================] - 1s 186us/sample - loss: 1.5670 - mse: 1.5670 - val_loss: 0.4256 - val_mse: 0.4256
Epoch 12/100
100/3021 [..............................] - ETA: 0s - loss: 1.4981 - mse: 1.4981
2000/3021 [==================>...........] - ETA: 0s - loss: 1.4034 - mse: 1.4034
3021/3021 [==============================] - 0s 162us/sample - loss: 1.4227 - mse: 1.4227 - val_loss: 0.3919 - val_mse: 0.3919
Epoch 13/100
100/3021 [..............................] - ETA: 0s - loss: 1.4046 - mse: 1.4046
2000/3021 [==================>...........] - ETA: 0s - loss: 1.3589 - mse: 1.3589
3021/3021 [==============================] - 0s 161us/sample - loss: 1.4095 - mse: 1.4095 - val_loss: 0.3463 - val_mse: 0.3463
Epoch 14/100
100/3021 [..............................] - ETA: 0s - loss: 1.3397 - mse: 1.3397
1400/3021 [============>.................] - ETA: 0s - loss: 1.4079 - mse: 1.4079
3021/3021 [==============================] - 0s 163us/sample - loss: 1.3933 - mse: 1.3933 - val_loss: 0.3134 - val_mse: 0.3134
Epoch 15/100
100/3021 [..............................] - ETA: 0s - loss: 1.0551 - mse: 1.0551
2100/3021 [===================>..........] - ETA: 0s - loss: 1.2575 - mse: 1.2575
3021/3021 [==============================] - 1s 174us/sample - loss: 1.2917 - mse: 1.2917 - val_loss: 0.2955 - val_mse: 0.2955
Epoch 16/100
100/3021 [..............................] - ETA: 0s - loss: 1.7537 - mse: 1.7537
1500/3021 [=============>................] - ETA: 0s - loss: 1.2979 - mse: 1.2979
3021/3021 [==============================] - 0s 156us/sample - loss: 1.2608 - mse: 1.2608 - val_loss: 0.2539 - val_mse: 0.2539
Epoch 17/100
100/3021 [..............................] - ETA: 0s - loss: 1.1672 - mse: 1.1672
2100/3021 [===================>..........] - ETA: 0s - loss: 1.1834 - mse: 1.1834
3021/3021 [==============================] - 1s 172us/sample - loss: 1.1725 - mse: 1.1725 - val_loss: 0.2379 - val_mse: 0.2379
Epoch 18/100
100/3021 [..............................] - ETA: 0s - loss: 1.5554 - mse: 1.5554
1400/3021 [============>.................] - ETA: 0s - loss: 1.2263 - mse: 1.2263
3021/3021 [==============================] - 0s 163us/sample - loss: 1.1857 - mse: 1.1857 - val_loss: 0.2282 - val_mse: 0.2282
Epoch 19/100
100/3021 [..............................] - ETA: 0s - loss: 1.0396 - mse: 1.0396
2200/3021 [====================>.........] - ETA: 0s - loss: 1.1706 - mse: 1.1706
3021/3021 [==============================] - 1s 204us/sample - loss: 1.1797 - mse: 1.1797 - val_loss: 0.2161 - val_mse: 0.2161
Epoch 20/100
100/3021 [..............................] - ETA: 0s - loss: 1.0173 - mse: 1.0173
2200/3021 [====================>.........] - ETA: 0s - loss: 1.1132 - mse: 1.1133
3021/3021 [==============================] - 0s 157us/sample - loss: 1.1120 - mse: 1.1120 - val_loss: 0.1986 - val_mse: 0.1986
Epoch 21/100
100/3021 [..............................] - ETA: 0s - loss: 1.1632 - mse: 1.1632
1800/3021 [================>.............] - ETA: 0s - loss: 1.0491 - mse: 1.0491
3021/3021 [==============================] - 1s 167us/sample - loss: 1.0691 - mse: 1.0691 - val_loss: 0.1854 - val_mse: 0.1854
Epoch 22/100
100/3021 [..............................] - ETA: 0s - loss: 1.0771 - mse: 1.0771
2100/3021 [===================>..........] - ETA: 0s - loss: 1.0998 - mse: 1.0998
3021/3021 [==============================] - 0s 157us/sample - loss: 1.1140 - mse: 1.1140 - val_loss: 0.1970 - val_mse: 0.1970
Epoch 23/100
100/3021 [..............................] - ETA: 0s - loss: 1.1032 - mse: 1.1032
2000/3021 [==================>...........] - ETA: 0s - loss: 1.0168 - mse: 1.0168
3021/3021 [==============================] - 0s 162us/sample - loss: 1.0276 - mse: 1.0276 - val_loss: 0.1639 - val_mse: 0.1639
Epoch 24/100
100/3021 [..............................] - ETA: 0s - loss: 1.1340 - mse: 1.1340
1800/3021 [================>.............] - ETA: 0s - loss: 1.0141 - mse: 1.0141
3021/3021 [==============================] - 0s 158us/sample - loss: 1.0441 - mse: 1.0441 - val_loss: 0.1727 - val_mse: 0.1727
Epoch 25/100
100/3021 [..............................] - ETA: 0s - loss: 0.9749 - mse: 0.9749
2300/3021 [=====================>........] - ETA: 0s - loss: 1.0413 - mse: 1.0413
3021/3021 [==============================] - 0s 159us/sample - loss: 1.0381 - mse: 1.0381 - val_loss: 0.1493 - val_mse: 0.1493
Epoch 26/100
100/3021 [..............................] - ETA: 0s - loss: 1.3505 - mse: 1.3505
2200/3021 [====================>.........] - ETA: 0s - loss: 0.9995 - mse: 0.9995
3021/3021 [==============================] - 0s 155us/sample - loss: 0.9935 - mse: 0.9935 - val_loss: 0.1554 - val_mse: 0.1554
Epoch 27/100
100/3021 [..............................] - ETA: 0s - loss: 1.0388 - mse: 1.0388
2000/3021 [==================>...........] - ETA: 0s - loss: 0.9776 - mse: 0.9776
3021/3021 [==============================] - 1s 170us/sample - loss: 0.9735 - mse: 0.9735 - val_loss: 0.1477 - val_mse: 0.1477
Epoch 28/100
100/3021 [..............................] - ETA: 0s - loss: 0.8262 - mse: 0.8262
2400/3021 [======================>.......] - ETA: 0s - loss: 0.9659 - mse: 0.9659
3021/3021 [==============================] - 0s 158us/sample - loss: 0.9481 - mse: 0.9481 - val_loss: 0.1490 - val_mse: 0.1490
Epoch 29/100
100/3021 [..............................] - ETA: 0s - loss: 0.9062 - mse: 0.9062
2100/3021 [===================>..........] - ETA: 0s - loss: 0.9372 - mse: 0.9372
3021/3021 [==============================] - 0s 159us/sample - loss: 0.9295 - mse: 0.9295 - val_loss: 0.1401 - val_mse: 0.1401
Epoch 30/100
100/3021 [..............................] - ETA: 0s - loss: 0.7020 - mse: 0.7020
2200/3021 [====================>.........] - ETA: 0s - loss: 0.9785 - mse: 0.9785
3021/3021 [==============================] - 0s 161us/sample - loss: 0.9738 - mse: 0.9738 - val_loss: 0.1259 - val_mse: 0.1259
Epoch 31/100
100/3021 [..............................] - ETA: 0s - loss: 0.8009 - mse: 0.8009
1900/3021 [=================>............] - ETA: 0s - loss: 0.9542 - mse: 0.9542
3021/3021 [==============================] - 0s 161us/sample - loss: 0.9374 - mse: 0.9374 - val_loss: 0.1238 - val_mse: 0.1238
Epoch 32/100
100/3021 [..............................] - ETA: 0s - loss: 0.9315 - mse: 0.9315
1300/3021 [===========>..................] - ETA: 0s - loss: 0.8933 - mse: 0.8933
3021/3021 [==============================] - 1s 166us/sample - loss: 0.8714 - mse: 0.8714 - val_loss: 0.1184 - val_mse: 0.1184
Epoch 33/100
100/3021 [..............................] - ETA: 0s - loss: 0.6907 - mse: 0.6907
2400/3021 [======================>.......] - ETA: 0s - loss: 0.8644 - mse: 0.8644
3021/3021 [==============================] - 1s 190us/sample - loss: 0.8653 - mse: 0.8653 - val_loss: 0.1249 - val_mse: 0.1249
Epoch 34/100
100/3021 [..............................] - ETA: 0s - loss: 0.7773 - mse: 0.7773
1300/3021 [===========>..................] - ETA: 0s - loss: 0.8422 - mse: 0.8422
3021/3021 [==============================] - 1s 172us/sample - loss: 0.8867 - mse: 0.8867 - val_loss: 0.1133 - val_mse: 0.1133
Epoch 35/100
100/3021 [..............................] - ETA: 0s - loss: 0.7328 - mse: 0.7328
2300/3021 [=====================>........] - ETA: 0s - loss: 0.8414 - mse: 0.8414
3021/3021 [==============================] - 0s 163us/sample - loss: 0.8596 - mse: 0.8596 - val_loss: 0.1217 - val_mse: 0.1217
Epoch 36/100
100/3021 [..............................] - ETA: 0s - loss: 0.8508 - mse: 0.8508
1200/3021 [==========>...................] - ETA: 0s - loss: 0.8185 - mse: 0.8185
3021/3021 [==============================] - 0s 160us/sample - loss: 0.8149 - mse: 0.8149 - val_loss: 0.1144 - val_mse: 0.1144
Epoch 37/100
100/3021 [..............................] - ETA: 0s - loss: 0.7620 - mse: 0.7620
2200/3021 [====================>.........] - ETA: 0s - loss: 0.8355 - mse: 0.8355
3021/3021 [==============================] - 0s 159us/sample - loss: 0.8488 - mse: 0.8488 - val_loss: 0.1071 - val_mse: 0.1071
Epoch 38/100
100/3021 [..............................] - ETA: 0s - loss: 0.6333 - mse: 0.6333
1300/3021 [===========>..................] - ETA: 0s - loss: 0.8099 - mse: 0.8099
3021/3021 [==============================] - 0s 159us/sample - loss: 0.8351 - mse: 0.8351 - val_loss: 0.1147 - val_mse: 0.1147
Epoch 39/100
100/3021 [..............................] - ETA: 0s - loss: 1.0648 - mse: 1.0648
2300/3021 [=====================>........] - ETA: 0s - loss: 0.7960 - mse: 0.7960
3021/3021 [==============================] - 0s 154us/sample - loss: 0.8144 - mse: 0.8144 - val_loss: 0.1153 - val_mse: 0.1153
Epoch 40/100
100/3021 [..............................] - ETA: 0s - loss: 0.7956 - mse: 0.7956
2200/3021 [====================>.........] - ETA: 0s - loss: 0.8200 - mse: 0.8200
3021/3021 [==============================] - 0s 152us/sample - loss: 0.8052 - mse: 0.8052 - val_loss: 0.1161 - val_mse: 0.1161
Epoch 41/100
100/3021 [..............................] - ETA: 0s - loss: 0.7671 - mse: 0.7671
2200/3021 [====================>.........] - ETA: 0s - loss: 0.7707 - mse: 0.7707
3021/3021 [==============================] - 0s 164us/sample - loss: 0.7960 - mse: 0.7960 - val_loss: 0.0941 - val_mse: 0.0941
Epoch 42/100
100/3021 [..............................] - ETA: 0s - loss: 0.7969 - mse: 0.7969
2400/3021 [======================>.......] - ETA: 0s - loss: 0.8298 - mse: 0.8298
3021/3021 [==============================] - 0s 152us/sample - loss: 0.8196 - mse: 0.8196 - val_loss: 0.1099 - val_mse: 0.1099
Epoch 43/100
100/3021 [..............................] - ETA: 0s - loss: 0.6979 - mse: 0.6979
1800/3021 [================>.............] - ETA: 0s - loss: 0.7909 - mse: 0.7909
3021/3021 [==============================] - 0s 164us/sample - loss: 0.7957 - mse: 0.7957 - val_loss: 0.0874 - val_mse: 0.0874
Epoch 44/100
100/3021 [..............................] - ETA: 0s - loss: 1.0498 - mse: 1.0498
1500/3021 [=============>................] - ETA: 0s - loss: 0.7942 - mse: 0.7942
3021/3021 [==============================] - 1s 183us/sample - loss: 0.7663 - mse: 0.7663 - val_loss: 0.0821 - val_mse: 0.0821
Epoch 45/100
100/3021 [..............................] - ETA: 0s - loss: 0.6849 - mse: 0.6849
1700/3021 [===============>..............] - ETA: 0s - loss: 0.7362 - mse: 0.7362
3021/3021 [==============================] - 0s 164us/sample - loss: 0.7306 - mse: 0.7306 - val_loss: 0.0798 - val_mse: 0.0798
Epoch 46/100
100/3021 [..............................] - ETA: 0s - loss: 0.9097 - mse: 0.9097
2200/3021 [====================>.........] - ETA: 0s - loss: 0.7655 - mse: 0.7655
3021/3021 [==============================] - 0s 154us/sample - loss: 0.7538 - mse: 0.7538 - val_loss: 0.1012 - val_mse: 0.1012
Epoch 47/100
100/3021 [..............................] - ETA: 0s - loss: 0.7308 - mse: 0.7308
1800/3021 [================>.............] - ETA: 0s - loss: 0.7606 - mse: 0.7606
3021/3021 [==============================] - 0s 158us/sample - loss: 0.7613 - mse: 0.7613 - val_loss: 0.0758 - val_mse: 0.0758
Epoch 48/100
100/3021 [..............................] - ETA: 0s - loss: 0.7044 - mse: 0.7044
2100/3021 [===================>..........] - ETA: 0s - loss: 0.7265 - mse: 0.7265
3021/3021 [==============================] - 1s 166us/sample - loss: 0.7106 - mse: 0.7106 - val_loss: 0.0778 - val_mse: 0.0778
Epoch 49/100
100/3021 [..............................] - ETA: 0s - loss: 0.7376 - mse: 0.7376
2200/3021 [====================>.........] - ETA: 0s - loss: 0.7127 - mse: 0.7127
3021/3021 [==============================] - 0s 159us/sample - loss: 0.7298 - mse: 0.7298 - val_loss: 0.0754 - val_mse: 0.0754
Epoch 50/100
100/3021 [..............................] - ETA: 0s - loss: 0.8272 - mse: 0.8272
1000/3021 [========>.....................] - ETA: 0s - loss: 0.7556 - mse: 0.7556
3000/3021 [============================>.] - ETA: 0s - loss: 0.7366 - mse: 0.7366
3021/3021 [==============================] - 1s 167us/sample - loss: 0.7363 - mse: 0.7363 - val_loss: 0.0734 - val_mse: 0.0734
Epoch 51/100
100/3021 [..............................] - ETA: 0s - loss: 0.6514 - mse: 0.6514
2200/3021 [====================>.........] - ETA: 0s - loss: 0.7084 - mse: 0.7084
3021/3021 [==============================] - 1s 167us/sample - loss: 0.7102 - mse: 0.7102 - val_loss: 0.0847 - val_mse: 0.0847
Epoch 52/100
100/3021 [..............................] - ETA: 0s - loss: 0.5354 - mse: 0.5354
2200/3021 [====================>.........] - ETA: 0s - loss: 0.7158 - mse: 0.7158
3021/3021 [==============================] - 0s 161us/sample - loss: 0.7218 - mse: 0.7218 - val_loss: 0.0874 - val_mse: 0.0874
Epoch 53/100
100/3021 [..............................] - ETA: 0s - loss: 0.7251 - mse: 0.7251
2000/3021 [==================>...........] - ETA: 0s - loss: 0.6888 - mse: 0.6888
3021/3021 [==============================] - 0s 157us/sample - loss: 0.6965 - mse: 0.6965 - val_loss: 0.0669 - val_mse: 0.0669
Epoch 54/100
100/3021 [..............................] - ETA: 0s - loss: 0.6642 - mse: 0.6642
2200/3021 [====================>.........] - ETA: 0s - loss: 0.7112 - mse: 0.7112
3021/3021 [==============================] - 0s 161us/sample - loss: 0.6894 - mse: 0.6894 - val_loss: 0.0928 - val_mse: 0.0928
Epoch 55/100
100/3021 [..............................] - ETA: 0s - loss: 0.6618 - mse: 0.6618
2100/3021 [===================>..........] - ETA: 0s - loss: 0.6743 - mse: 0.6743
3021/3021 [==============================] - 1s 167us/sample - loss: 0.6772 - mse: 0.6772 - val_loss: 0.0758 - val_mse: 0.0758
Epoch 56/100
100/3021 [..............................] - ETA: 0s - loss: 0.5720 - mse: 0.5720
1400/3021 [============>.................] - ETA: 0s - loss: 0.6737 - mse: 0.6737
3021/3021 [==============================] - 0s 162us/sample - loss: 0.6650 - mse: 0.6650 - val_loss: 0.0657 - val_mse: 0.0657
Epoch 57/100
100/3021 [..............................] - ETA: 0s - loss: 0.8239 - mse: 0.8239
1900/3021 [=================>............] - ETA: 0s - loss: 0.6784 - mse: 0.6784
3021/3021 [==============================] - 0s 160us/sample - loss: 0.6781 - mse: 0.6781 - val_loss: 0.0892 - val_mse: 0.0892
Epoch 58/100
100/3021 [..............................] - ETA: 0s - loss: 0.8305 - mse: 0.8305
1900/3021 [=================>............] - ETA: 0s - loss: 0.6703 - mse: 0.6703
3021/3021 [==============================] - 0s 153us/sample - loss: 0.6709 - mse: 0.6709 - val_loss: 0.0748 - val_mse: 0.0748
Epoch 59/100
100/3021 [..............................] - ETA: 0s - loss: 0.7639 - mse: 0.7639
1200/3021 [==========>...................] - ETA: 0s - loss: 0.7090 - mse: 0.7090
3021/3021 [==============================] - 1s 174us/sample - loss: 0.6722 - mse: 0.6722 - val_loss: 0.0641 - val_mse: 0.0641
Epoch 60/100
100/3021 [..............................] - ETA: 0s - loss: 0.6020 - mse: 0.6020
1800/3021 [================>.............] - ETA: 0s - loss: 0.6966 - mse: 0.6966
3021/3021 [==============================] - 0s 157us/sample - loss: 0.6800 - mse: 0.6800 - val_loss: 0.0669 - val_mse: 0.0669
Epoch 61/100
100/3021 [..............................] - ETA: 0s - loss: 0.6512 - mse: 0.6512
2300/3021 [=====================>........] - ETA: 0s - loss: 0.6706 - mse: 0.6706
3021/3021 [==============================] - 0s 162us/sample - loss: 0.6619 - mse: 0.6619 - val_loss: 0.0629 - val_mse: 0.0629
Epoch 62/100
100/3021 [..............................] - ETA: 0s - loss: 0.5837 - mse: 0.5837
2300/3021 [=====================>........] - ETA: 0s - loss: 0.6356 - mse: 0.6356
3021/3021 [==============================] - 0s 154us/sample - loss: 0.6315 - mse: 0.6315 - val_loss: 0.0675 - val_mse: 0.0675
Epoch 63/100
100/3021 [..............................] - ETA: 0s - loss: 0.5507 - mse: 0.5507
2000/3021 [==================>...........] - ETA: 0s - loss: 0.6853 - mse: 0.6853
3021/3021 [==============================] - 1s 166us/sample - loss: 0.6613 - mse: 0.6613 - val_loss: 0.0637 - val_mse: 0.0637
Epoch 64/100
100/3021 [..............................] - ETA: 0s - loss: 0.6789 - mse: 0.6789
2000/3021 [==================>...........] - ETA: 0s - loss: 0.6431 - mse: 0.6431
3021/3021 [==============================] - 0s 159us/sample - loss: 0.6218 - mse: 0.6218 - val_loss: 0.0556 - val_mse: 0.0556
Epoch 65/100
100/3021 [..............................] - ETA: 0s - loss: 0.5835 - mse: 0.5835
1500/3021 [=============>................] - ETA: 0s - loss: 0.6251 - mse: 0.6251
3021/3021 [==============================] - 0s 158us/sample - loss: 0.6231 - mse: 0.6231 - val_loss: 0.0668 - val_mse: 0.0668
Epoch 66/100
100/3021 [..............................] - ETA: 0s - loss: 0.5689 - mse: 0.5689
2300/3021 [=====================>........] - ETA: 0s - loss: 0.6024 - mse: 0.6024
3021/3021 [==============================] - 0s 158us/sample - loss: 0.6177 - mse: 0.6177 - val_loss: 0.0643 - val_mse: 0.0643
Epoch 67/100
100/3021 [..............................] - ETA: 0s - loss: 0.5920 - mse: 0.5920
2100/3021 [===================>..........] - ETA: 0s - loss: 0.6476 - mse: 0.6476
3021/3021 [==============================] - 0s 157us/sample - loss: 0.6468 - mse: 0.6468 - val_loss: 0.0562 - val_mse: 0.0562
Epoch 68/100
100/3021 [..............................] - ETA: 0s - loss: 0.8102 - mse: 0.8102
2200/3021 [====================>.........] - ETA: 0s - loss: 0.6255 - mse: 0.6255
3021/3021 [==============================] - 0s 156us/sample - loss: 0.6311 - mse: 0.6311 - val_loss: 0.0663 - val_mse: 0.0663
Epoch 69/100
100/3021 [..............................] - ETA: 0s - loss: 0.5142 - mse: 0.5142
2000/3021 [==================>...........] - ETA: 0s - loss: 0.6335 - mse: 0.6335
3021/3021 [==============================] - 0s 151us/sample - loss: 0.6279 - mse: 0.6279 - val_loss: 0.0525 - val_mse: 0.0525
Epoch 70/100
100/3021 [..............................] - ETA: 0s - loss: 0.7114 - mse: 0.7114
2000/3021 [==================>...........] - ETA: 0s - loss: 0.6347 - mse: 0.6347
3021/3021 [==============================] - 0s 163us/sample - loss: 0.6316 - mse: 0.6316 - val_loss: 0.0562 - val_mse: 0.0562
Epoch 71/100
100/3021 [..............................] - ETA: 0s - loss: 0.7064 - mse: 0.7064
1900/3021 [=================>............] - ETA: 0s - loss: 0.6073 - mse: 0.6073
3021/3021 [==============================] - 0s 163us/sample - loss: 0.5985 - mse: 0.5985 - val_loss: 0.0586 - val_mse: 0.0586
Epoch 72/100
100/3021 [..............................] - ETA: 0s - loss: 0.7893 - mse: 0.7893
2300/3021 [=====================>........] - ETA: 0s - loss: 0.6307 - mse: 0.6307
3021/3021 [==============================] - 0s 154us/sample - loss: 0.6276 - mse: 0.6276 - val_loss: 0.0587 - val_mse: 0.0587
Epoch 73/100
100/3021 [..............................] - ETA: 0s - loss: 0.6043 - mse: 0.6043
1100/3021 [=========>....................] - ETA: 0s - loss: 0.6179 - mse: 0.6179
3021/3021 [==============================] - 0s 158us/sample - loss: 0.6016 - mse: 0.6016 - val_loss: 0.0590 - val_mse: 0.0590
Epoch 74/100
100/3021 [..............................] - ETA: 0s - loss: 0.6346 - mse: 0.6346
2200/3021 [====================>.........] - ETA: 0s - loss: 0.5859 - mse: 0.5859
3021/3021 [==============================] - 0s 160us/sample - loss: 0.5936 - mse: 0.5936 - val_loss: 0.0474 - val_mse: 0.0474
Epoch 75/100
100/3021 [..............................] - ETA: 0s - loss: 0.4972 - mse: 0.4972
2100/3021 [===================>..........] - ETA: 0s - loss: 0.6065 - mse: 0.6065
3021/3021 [==============================] - 0s 162us/sample - loss: 0.6005 - mse: 0.6005 - val_loss: 0.0528 - val_mse: 0.0528
Epoch 76/100
100/3021 [..............................] - ETA: 0s - loss: 0.4781 - mse: 0.4781
2200/3021 [====================>.........] - ETA: 0s - loss: 0.5932 - mse: 0.5932
3021/3021 [==============================] - 0s 162us/sample - loss: 0.5894 - mse: 0.5894 - val_loss: 0.0664 - val_mse: 0.0664
Epoch 77/100
100/3021 [..............................] - ETA: 0s - loss: 0.5062 - mse: 0.5062
1800/3021 [================>.............] - ETA: 0s - loss: 0.5592 - mse: 0.5592
3021/3021 [==============================] - 0s 165us/sample - loss: 0.5608 - mse: 0.5608 - val_loss: 0.0533 - val_mse: 0.0533
Epoch 78/100
100/3021 [..............................] - ETA: 0s - loss: 0.5741 - mse: 0.5741
1800/3021 [================>.............] - ETA: 0s - loss: 0.6006 - mse: 0.6006
3021/3021 [==============================] - 0s 164us/sample - loss: 0.5769 - mse: 0.5769 - val_loss: 0.0648 - val_mse: 0.0648
Epoch 79/100
100/3021 [..............................] - ETA: 0s - loss: 0.6071 - mse: 0.6071
1400/3021 [============>.................] - ETA: 0s - loss: 0.5841 - mse: 0.5841
3021/3021 [==============================] - 0s 161us/sample - loss: 0.5974 - mse: 0.5974 - val_loss: 0.0622 - val_mse: 0.0622
Epoch 80/100
100/3021 [..............................] - ETA: 0s - loss: 0.6131 - mse: 0.6131
1900/3021 [=================>............] - ETA: 0s - loss: 0.5849 - mse: 0.5849
3021/3021 [==============================] - 1s 172us/sample - loss: 0.5914 - mse: 0.5914 - val_loss: 0.0580 - val_mse: 0.0580
Epoch 81/100
100/3021 [..............................] - ETA: 0s - loss: 0.6633 - mse: 0.6633
1200/3021 [==========>...................] - ETA: 0s - loss: 0.5872 - mse: 0.5872
3021/3021 [==============================] - 0s 163us/sample - loss: 0.6033 - mse: 0.6033 - val_loss: 0.0497 - val_mse: 0.0497
Epoch 82/100
100/3021 [..............................] - ETA: 0s - loss: 0.4776 - mse: 0.4776
2300/3021 [=====================>........] - ETA: 0s - loss: 0.5771 - mse: 0.5771
3021/3021 [==============================] - 0s 153us/sample - loss: 0.5720 - mse: 0.5720 - val_loss: 0.0539 - val_mse: 0.0539
Epoch 83/100
100/3021 [..............................] - ETA: 0s - loss: 0.6038 - mse: 0.6038
1900/3021 [=================>............] - ETA: 0s - loss: 0.5597 - mse: 0.5597
3021/3021 [==============================] - 0s 147us/sample - loss: 0.5663 - mse: 0.5663 - val_loss: 0.0532 - val_mse: 0.0532
Epoch 84/100
100/3021 [..............................] - ETA: 0s - loss: 0.4945 - mse: 0.4945
1900/3021 [=================>............] - ETA: 0s - loss: 0.5875 - mse: 0.5875
3021/3021 [==============================] - 0s 159us/sample - loss: 0.5856 - mse: 0.5856 - val_loss: 0.0514 - val_mse: 0.0514
Epoch 85/100
100/3021 [..............................] - ETA: 0s - loss: 0.5082 - mse: 0.5082
2200/3021 [====================>.........] - ETA: 0s - loss: 0.5500 - mse: 0.5500
3021/3021 [==============================] - 0s 158us/sample - loss: 0.5452 - mse: 0.5452 - val_loss: 0.0460 - val_mse: 0.0460
Epoch 86/100
100/3021 [..............................] - ETA: 0s - loss: 0.5661 - mse: 0.5661
1800/3021 [================>.............] - ETA: 0s - loss: 0.5674 - mse: 0.5674
3021/3021 [==============================] - 1s 167us/sample - loss: 0.5676 - mse: 0.5676 - val_loss: 0.0649 - val_mse: 0.0649
Epoch 87/100
100/3021 [..............................] - ETA: 0s - loss: 0.5642 - mse: 0.5642
1100/3021 [=========>....................] - ETA: 0s - loss: 0.5334 - mse: 0.5334
3021/3021 [==============================] - 0s 164us/sample - loss: 0.5563 - mse: 0.5563 - val_loss: 0.0830 - val_mse: 0.0830
Epoch 88/100
100/3021 [..............................] - ETA: 0s - loss: 0.5744 - mse: 0.5744
2300/3021 [=====================>........] - ETA: 0s - loss: 0.5484 - mse: 0.5484
3021/3021 [==============================] - 0s 154us/sample - loss: 0.5635 - mse: 0.5635 - val_loss: 0.0777 - val_mse: 0.0777
Epoch 89/100
100/3021 [..............................] - ETA: 0s - loss: 0.6344 - mse: 0.6344
2200/3021 [====================>.........] - ETA: 0s - loss: 0.5457 - mse: 0.5457
3021/3021 [==============================] - 0s 155us/sample - loss: 0.5561 - mse: 0.5561 - val_loss: 0.0553 - val_mse: 0.0553
Epoch 90/100
100/3021 [..............................] - ETA: 0s - loss: 0.6252 - mse: 0.6252
1900/3021 [=================>............] - ETA: 0s - loss: 0.5345 - mse: 0.5345
3021/3021 [==============================] - 1s 176us/sample - loss: 0.5423 - mse: 0.5423 - val_loss: 0.0545 - val_mse: 0.0545
Epoch 91/100
100/3021 [..............................] - ETA: 0s - loss: 0.4484 - mse: 0.4484
2200/3021 [====================>.........] - ETA: 0s - loss: 0.5423 - mse: 0.5423
3021/3021 [==============================] - 0s 154us/sample - loss: 0.5509 - mse: 0.5509 - val_loss: 0.0468 - val_mse: 0.0468
Epoch 92/100
100/3021 [..............................] - ETA: 0s - loss: 0.5238 - mse: 0.5238
2000/3021 [==================>...........] - ETA: 0s - loss: 0.5847 - mse: 0.5847
3021/3021 [==============================] - 1s 168us/sample - loss: 0.5554 - mse: 0.5554 - val_loss: 0.0550 - val_mse: 0.0550
Epoch 93/100
100/3021 [..............................] - ETA: 0s - loss: 0.4928 - mse: 0.4928
1700/3021 [===============>..............] - ETA: 0s - loss: 0.5687 - mse: 0.5687
3021/3021 [==============================] - 1s 174us/sample - loss: 0.5760 - mse: 0.5760 - val_loss: 0.0533 - val_mse: 0.0533
Epoch 94/100
100/3021 [..............................] - ETA: 0s - loss: 0.4810 - mse: 0.4810
1700/3021 [===============>..............] - ETA: 0s - loss: 0.5415 - mse: 0.5415
3021/3021 [==============================] - 1s 194us/sample - loss: 0.5457 - mse: 0.5457 - val_loss: 0.0681 - val_mse: 0.0681
Epoch 95/100
100/3021 [..............................] - ETA: 0s - loss: 0.4194 - mse: 0.4194
1900/3021 [=================>............] - ETA: 0s - loss: 0.5545 - mse: 0.5545
3021/3021 [==============================] - 1s 171us/sample - loss: 0.5689 - mse: 0.5689 - val_loss: 0.0726 - val_mse: 0.0726
Epoch 96/100
100/3021 [..............................] - ETA: 0s - loss: 0.5697 - mse: 0.5697
1200/3021 [==========>...................] - ETA: 0s - loss: 0.5421 - mse: 0.5421
2500/3021 [=======================>......] - ETA: 0s - loss: 0.5621 - mse: 0.5621
3021/3021 [==============================] - 1s 214us/sample - loss: 0.5674 - mse: 0.5674 - val_loss: 0.0407 - val_mse: 0.0407
Epoch 97/100
100/3021 [..............................] - ETA: 0s - loss: 0.6012 - mse: 0.6012
1700/3021 [===============>..............] - ETA: 0s - loss: 0.5384 - mse: 0.5384
3021/3021 [==============================] - 0s 163us/sample - loss: 0.5433 - mse: 0.5433 - val_loss: 0.0494 - val_mse: 0.0494
Epoch 98/100
100/3021 [..............................] - ETA: 0s - loss: 0.4947 - mse: 0.4947
2200/3021 [====================>.........] - ETA: 0s - loss: 0.5448 - mse: 0.5448
3021/3021 [==============================] - 0s 165us/sample - loss: 0.5469 - mse: 0.5469 - val_loss: 0.0454 - val_mse: 0.0454
Epoch 99/100
100/3021 [..............................] - ETA: 0s - loss: 0.5465 - mse: 0.5465
1600/3021 [==============>...............] - ETA: 0s - loss: 0.5492 - mse: 0.5492
3021/3021 [==============================] - 0s 163us/sample - loss: 0.5270 - mse: 0.5270 - val_loss: 0.0460 - val_mse: 0.0460
Epoch 100/100
100/3021 [..............................] - ETA: 0s - loss: 0.4872 - mse: 0.4872
2200/3021 [====================>.........] - ETA: 0s - loss: 0.5410 - mse: 0.5410
3021/3021 [==============================] - 0s 163us/sample - loss: 0.5354 - mse: 0.5354 - val_loss: 0.0435 - val_mse: 0.0435Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-05-04T01-03-33Z
Training run 24/46 (flags = list(392, 128, 0.001, 100, 50, "tanh", "sigmoid", 0.2, 0.1))
Using run directory runs/2020-05-04T01-04-27Z
> FLAGS <- flags(
+ flag_numeric("nodes1", 128),
+ flag_numeric("nodes2", 128),
+ flag_numeric("batch_size", 100),
+ flag_string("activation1" .... [TRUNCATED]
> model = keras_model_sequential()
> model %>%
+ layer_dense(units=FLAGS$nodes1, activation=FLAGS$activation1, input_shape=dim(efw_train2)[2]) %>%
+ layer_dropout(FLAGS$dropout1) %> .... [TRUNCATED]
> model %>% compile(
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ loss = 'mse',
+ metrics = c('mse')
+ )
> model %>% fit(
+ as.matrix(efw_train2), train2Label,
+ epochs=FLAGS$epochs,
+ batch_size=FLAGS$batch_size,
+ validation_data=list(as.matrix( .... [TRUNCATED]
Train on 3021 samples, validate on 334 samples
Epoch 1/50
100/3021 [..............................] - ETA: 8s - loss: 45.0059 - mse: 45.0059
1600/3021 [==============>...............] - ETA: 0s - loss: 38.3896 - mse: 38.3896
3021/3021 [==============================] - 1s 290us/sample - loss: 33.3560 - mse: 33.3560 - val_loss: 22.1375 - val_mse: 22.1375
Epoch 2/50
100/3021 [..............................] - ETA: 0s - loss: 21.2916 - mse: 21.2916
1000/3021 [========>.....................] - ETA: 0s - loss: 18.2164 - mse: 18.2164
2700/3021 [=========================>....] - ETA: 0s - loss: 12.4692 - mse: 12.4692
3021/3021 [==============================] - 1s 181us/sample - loss: 11.5794 - mse: 11.5794 - val_loss: 3.0090 - val_mse: 3.0090
Epoch 3/50
100/3021 [..............................] - ETA: 0s - loss: 3.0192 - mse: 3.0192
1500/3021 [=============>................] - ETA: 0s - loss: 1.2754 - mse: 1.2754
2800/3021 [==========================>...] - ETA: 0s - loss: 0.8325 - mse: 0.8325
3021/3021 [==============================] - 1s 213us/sample - loss: 0.7943 - mse: 0.7943 - val_loss: 0.1720 - val_mse: 0.1720
Epoch 4/50
100/3021 [..............................] - ETA: 0s - loss: 0.2397 - mse: 0.2397
1500/3021 [=============>................] - ETA: 0s - loss: 0.2414 - mse: 0.2414
3021/3021 [==============================] - 1s 179us/sample - loss: 0.2180 - mse: 0.2180 - val_loss: 0.0737 - val_mse: 0.0737
Epoch 5/50
100/3021 [..............................] - ETA: 0s - loss: 0.1341 - mse: 0.1341
1400/3021 [============>.................] - ETA: 0s - loss: 0.1828 - mse: 0.1828
3000/3021 [============================>.] - ETA: 0s - loss: 0.1830 - mse: 0.1830
3021/3021 [==============================] - 1s 173us/sample - loss: 0.1837 - mse: 0.1837 - val_loss: 0.0745 - val_mse: 0.0745
Epoch 6/50
100/3021 [..............................] - ETA: 0s - loss: 0.2114 - mse: 0.2114
1600/3021 [==============>...............] - ETA: 0s - loss: 0.1766 - mse: 0.1766
3021/3021 [==============================] - 1s 169us/sample - loss: 0.1725 - mse: 0.1725 - val_loss: 0.0647 - val_mse: 0.0647
Epoch 7/50
100/3021 [..............................] - ETA: 0s - loss: 0.1819 - mse: 0.1819
1500/3021 [=============>................] - ETA: 0s - loss: 0.1662 - mse: 0.1662
2900/3021 [===========================>..] - ETA: 0s - loss: 0.1639 - mse: 0.1639
3021/3021 [==============================] - 1s 176us/sample - loss: 0.1618 - mse: 0.1618 - val_loss: 0.0569 - val_mse: 0.0569
Epoch 8/50
100/3021 [..............................] - ETA: 0s - loss: 0.1752 - mse: 0.1752
1200/3021 [==========>...................] - ETA: 0s - loss: 0.1533 - mse: 0.1533
2900/3021 [===========================>..] - ETA: 0s - loss: 0.1565 - mse: 0.1565
3021/3021 [==============================] - 1s 177us/sample - loss: 0.1564 - mse: 0.1564 - val_loss: 0.0644 - val_mse: 0.0644
Epoch 9/50
100/3021 [..............................] - ETA: 0s - loss: 0.2070 - mse: 0.2070
1800/3021 [================>.............] - ETA: 0s - loss: 0.1636 - mse: 0.1636
3021/3021 [==============================] - 1s 170us/sample - loss: 0.1584 - mse: 0.1584 - val_loss: 0.0567 - val_mse: 0.0567
Epoch 10/50
100/3021 [..............................] - ETA: 0s - loss: 0.1487 - mse: 0.1487
1500/3021 [=============>................] - ETA: 0s - loss: 0.1546 - mse: 0.1546
2900/3021 [===========================>..] - ETA: 0s - loss: 0.1502 - mse: 0.1502
3021/3021 [==============================] - 1s 184us/sample - loss: 0.1507 - mse: 0.1507 - val_loss: 0.0486 - val_mse: 0.0486
Epoch 11/50
100/3021 [..............................] - ETA: 0s - loss: 0.1328 - mse: 0.1328
1500/3021 [=============>................] - ETA: 0s - loss: 0.1602 - mse: 0.1602
3000/3021 [============================>.] - ETA: 0s - loss: 0.1488 - mse: 0.1488
3021/3021 [==============================] - 1s 173us/sample - loss: 0.1485 - mse: 0.1485 - val_loss: 0.0573 - val_mse: 0.0573
Epoch 12/50
100/3021 [..............................] - ETA: 0s - loss: 0.1447 - mse: 0.1447
1700/3021 [===============>..............] - ETA: 0s - loss: 0.1559 - mse: 0.1559
3021/3021 [==============================] - 1s 166us/sample - loss: 0.1508 - mse: 0.1508 - val_loss: 0.0504 - val_mse: 0.0504
Epoch 13/50
100/3021 [..............................] - ETA: 0s - loss: 0.1165 - mse: 0.1165
1700/3021 [===============>..............] - ETA: 0s - loss: 0.1505 - mse: 0.1505
3021/3021 [==============================] - 1s 167us/sample - loss: 0.1478 - mse: 0.1478 - val_loss: 0.0743 - val_mse: 0.0743
Epoch 14/50
100/3021 [..............................] - ETA: 0s - loss: 0.2074 - mse: 0.2074
1200/3021 [==========>...................] - ETA: 0s - loss: 0.1432 - mse: 0.1432
2600/3021 [========================>.....] - ETA: 0s - loss: 0.1566 - mse: 0.1566
3021/3021 [==============================] - 1s 171us/sample - loss: 0.1579 - mse: 0.1579 - val_loss: 0.0540 - val_mse: 0.0540
Epoch 15/50
100/3021 [..............................] - ETA: 0s - loss: 0.2171 - mse: 0.2171
1600/3021 [==============>...............] - ETA: 0s - loss: 0.1369 - mse: 0.1369
3021/3021 [==============================] - 1s 169us/sample - loss: 0.1396 - mse: 0.1396 - val_loss: 0.0525 - val_mse: 0.0525
Epoch 16/50
100/3021 [..............................] - ETA: 0s - loss: 0.1250 - mse: 0.1250
1600/3021 [==============>...............] - ETA: 0s - loss: 0.1392 - mse: 0.1392
3021/3021 [==============================] - 1s 174us/sample - loss: 0.1356 - mse: 0.1356 - val_loss: 0.0460 - val_mse: 0.0460
Epoch 17/50
100/3021 [..............................] - ETA: 0s - loss: 0.0952 - mse: 0.0952
900/3021 [=======>......................] - ETA: 0s - loss: 0.1283 - mse: 0.1283
2400/3021 [======================>.......] - ETA: 0s - loss: 0.1331 - mse: 0.1331
3021/3021 [==============================] - 1s 179us/sample - loss: 0.1293 - mse: 0.1293 - val_loss: 0.0500 - val_mse: 0.0500
Epoch 18/50
100/3021 [..............................] - ETA: 0s - loss: 0.1024 - mse: 0.1024
1700/3021 [===============>..............] - ETA: 0s - loss: 0.1422 - mse: 0.1422
3021/3021 [==============================] - 1s 178us/sample - loss: 0.1319 - mse: 0.1319 - val_loss: 0.0523 - val_mse: 0.0523
Epoch 19/50
100/3021 [..............................] - ETA: 0s - loss: 0.1047 - mse: 0.1047
1800/3021 [================>.............] - ETA: 0s - loss: 0.1311 - mse: 0.1311
3021/3021 [==============================] - 1s 174us/sample - loss: 0.1275 - mse: 0.1275 - val_loss: 0.0456 - val_mse: 0.0456
Epoch 20/50
100/3021 [..............................] - ETA: 0s - loss: 0.1192 - mse: 0.1192
1300/3021 [===========>..................] - ETA: 0s - loss: 0.1237 - mse: 0.1237
2000/3021 [==================>...........] - ETA: 0s - loss: 0.1239 - mse: 0.1239
3000/3021 [============================>.] - ETA: 0s - loss: 0.1249 - mse: 0.1249
3021/3021 [==============================] - 1s 241us/sample - loss: 0.1246 - mse: 0.1246 - val_loss: 0.0490 - val_mse: 0.0490
Epoch 21/50
100/3021 [..............................] - ETA: 0s - loss: 0.1064 - mse: 0.1064
1100/3021 [=========>....................] - ETA: 0s - loss: 0.1347 - mse: 0.1347
2200/3021 [====================>.........] - ETA: 0s - loss: 0.1280 - mse: 0.1280
3021/3021 [==============================] - 1s 214us/sample - loss: 0.1253 - mse: 0.1253 - val_loss: 0.0451 - val_mse: 0.0451
Epoch 22/50
100/3021 [..............................] - ETA: 0s - loss: 0.1623 - mse: 0.1623
1300/3021 [===========>..................] - ETA: 0s - loss: 0.1230 - mse: 0.1230
2500/3021 [=======================>......] - ETA: 0s - loss: 0.1261 - mse: 0.1261
3021/3021 [==============================] - 1s 194us/sample - loss: 0.1239 - mse: 0.1239 - val_loss: 0.0548 - val_mse: 0.0548
Epoch 23/50
100/3021 [..............................] - ETA: 0s - loss: 0.1175 - mse: 0.1175
1400/3021 [============>.................] - ETA: 0s - loss: 0.1265 - mse: 0.1265
2900/3021 [===========================>..] - ETA: 0s - loss: 0.1268 - mse: 0.1268
3021/3021 [==============================] - 1s 177us/sample - loss: 0.1266 - mse: 0.1266 - val_loss: 0.0486 - val_mse: 0.0486
Epoch 24/50
100/3021 [..............................] - ETA: 0s - loss: 0.1235 - mse: 0.1235
1200/3021 [==========>...................] - ETA: 0s - loss: 0.1164 - mse: 0.1164
2700/3021 [=========================>....] - ETA: 0s - loss: 0.1221 - mse: 0.1221
3021/3021 [==============================] - 1s 179us/sample - loss: 0.1234 - mse: 0.1234 - val_loss: 0.0471 - val_mse: 0.0471
Epoch 25/50
100/3021 [..............................] - ETA: 0s - loss: 0.1326 - mse: 0.1326
1400/3021 [============>.................] - ETA: 0s - loss: 0.1111 - mse: 0.1111
2800/3021 [==========================>...] - ETA: 0s - loss: 0.1178 - mse: 0.1178
3021/3021 [==============================] - 1s 181us/sample - loss: 0.1172 - mse: 0.1172 - val_loss: 0.0451 - val_mse: 0.0451
Epoch 26/50
100/3021 [..............................] - ETA: 0s - loss: 0.1190 - mse: 0.1190
1500/3021 [=============>................] - ETA: 0s - loss: 0.1185 - mse: 0.1185
3021/3021 [==============================] - 1s 177us/sample - loss: 0.1138 - mse: 0.1138 - val_loss: 0.0392 - val_mse: 0.0392
Epoch 27/50
100/3021 [..............................] - ETA: 0s - loss: 0.1114 - mse: 0.1114
1600/3021 [==============>...............] - ETA: 0s - loss: 0.1153 - mse: 0.1153
3000/3021 [============================>.] - ETA: 0s - loss: 0.1168 - mse: 0.1168
3021/3021 [==============================] - 1s 172us/sample - loss: 0.1170 - mse: 0.1170 - val_loss: 0.0531 - val_mse: 0.0531
Epoch 28/50
100/3021 [..............................] - ETA: 0s - loss: 0.1058 - mse: 0.1058
1600/3021 [==============>...............] - ETA: 0s - loss: 0.1173 - mse: 0.1173
3021/3021 [==============================] - 1s 176us/sample - loss: 0.1136 - mse: 0.1136 - val_loss: 0.0507 - val_mse: 0.0507
Epoch 29/50
100/3021 [..............................] - ETA: 0s - loss: 0.1839 - mse: 0.1839
1500/3021 [=============>................] - ETA: 0s - loss: 0.1144 - mse: 0.1144
2800/3021 [==========================>...] - ETA: 0s - loss: 0.1091 - mse: 0.1091
3021/3021 [==============================] - 1s 192us/sample - loss: 0.1099 - mse: 0.1099 - val_loss: 0.0440 - val_mse: 0.0440
Epoch 30/50
100/3021 [..............................] - ETA: 0s - loss: 0.1006 - mse: 0.1006
1000/3021 [========>.....................] - ETA: 0s - loss: 0.1236 - mse: 0.1236
2700/3021 [=========================>....] - ETA: 0s - loss: 0.1155 - mse: 0.1155
3021/3021 [==============================] - 1s 192us/sample - loss: 0.1160 - mse: 0.1160 - val_loss: 0.0485 - val_mse: 0.0485
Epoch 31/50
100/3021 [..............................] - ETA: 0s - loss: 0.1062 - mse: 0.1062
1300/3021 [===========>..................] - ETA: 0s - loss: 0.1193 - mse: 0.1193
2900/3021 [===========================>..] - ETA: 0s - loss: 0.1145 - mse: 0.1145
3021/3021 [==============================] - 1s 185us/sample - loss: 0.1143 - mse: 0.1143 - val_loss: 0.0424 - val_mse: 0.0424
Epoch 32/50
100/3021 [..............................] - ETA: 0s - loss: 0.1099 - mse: 0.1099
1600/3021 [==============>...............] - ETA: 0s - loss: 0.1144 - mse: 0.1144
3021/3021 [==============================] - 1s 172us/sample - loss: 0.1125 - mse: 0.1125 - val_loss: 0.0450 - val_mse: 0.0450
Epoch 33/50
100/3021 [..............................] - ETA: 0s - loss: 0.0953 - mse: 0.0953
1500/3021 [=============>................] - ETA: 0s - loss: 0.1021 - mse: 0.1021
2900/3021 [===========================>..] - ETA: 0s - loss: 0.1089 - mse: 0.1089
3021/3021 [==============================] - 1s 191us/sample - loss: 0.1082 - mse: 0.1082 - val_loss: 0.0650 - val_mse: 0.0650
Epoch 34/50
100/3021 [..............................] - ETA: 0s - loss: 0.1434 - mse: 0.1434
1700/3021 [===============>..............] - ETA: 0s - loss: 0.1094 - mse: 0.1094
3021/3021 [==============================] - 1s 170us/sample - loss: 0.1088 - mse: 0.1088 - val_loss: 0.0571 - val_mse: 0.0571
Epoch 35/50
100/3021 [..............................] - ETA: 0s - loss: 0.1033 - mse: 0.1033
1400/3021 [============>.................] - ETA: 0s - loss: 0.0996 - mse: 0.0996
3000/3021 [============================>.] - ETA: 0s - loss: 0.1049 - mse: 0.1049
3021/3021 [==============================] - 1s 175us/sample - loss: 0.1046 - mse: 0.1046 - val_loss: 0.0586 - val_mse: 0.0586
Epoch 36/50
100/3021 [..............................] - ETA: 0s - loss: 0.1610 - mse: 0.1610
1300/3021 [===========>..................] - ETA: 0s - loss: 0.1075 - mse: 0.1075
2500/3021 [=======================>......] - ETA: 0s - loss: 0.1051 - mse: 0.1051
3021/3021 [==============================] - 1s 217us/sample - loss: 0.1038 - mse: 0.1038 - val_loss: 0.0506 - val_mse: 0.0506
Epoch 37/50
100/3021 [..............................] - ETA: 0s - loss: 0.0851 - mse: 0.0851
1500/3021 [=============>................] - ETA: 0s - loss: 0.0937 - mse: 0.0937
3021/3021 [==============================] - 1s 178us/sample - loss: 0.1014 - mse: 0.1014 - val_loss: 0.0493 - val_mse: 0.0493
Epoch 38/50
100/3021 [..............................] - ETA: 0s - loss: 0.0915 - mse: 0.0915
1600/3021 [==============>...............] - ETA: 0s - loss: 0.1132 - mse: 0.1132
3021/3021 [==============================] - 1s 174us/sample - loss: 0.1065 - mse: 0.1065 - val_loss: 0.0623 - val_mse: 0.0623
Epoch 39/50
100/3021 [..............................] - ETA: 0s - loss: 0.1033 - mse: 0.1033
1500/3021 [=============>................] - ETA: 0s - loss: 0.0988 - mse: 0.0988
3021/3021 [==============================] - 1s 176us/sample - loss: 0.1017 - mse: 0.1017 - val_loss: 0.0526 - val_mse: 0.0526
Epoch 40/50
100/3021 [..............................] - ETA: 0s - loss: 0.0700 - mse: 0.0700
1100/3021 [=========>....................] - ETA: 0s - loss: 0.0954 - mse: 0.0954
2400/3021 [======================>.......] - ETA: 0s - loss: 0.1021 - mse: 0.1021
3021/3021 [==============================] - 1s 184us/sample - loss: 0.1004 - mse: 0.1004 - val_loss: 0.0508 - val_mse: 0.0508
Epoch 41/50
100/3021 [..............................] - ETA: 0s - loss: 0.1059 - mse: 0.1059
1700/3021 [===============>..............] - ETA: 0s - loss: 0.0944 - mse: 0.0944
3021/3021 [==============================] - 1s 173us/sample - loss: 0.0944 - mse: 0.0944 - val_loss: 0.0414 - val_mse: 0.0414
Epoch 42/50
100/3021 [..............................] - ETA: 0s - loss: 0.1543 - mse: 0.1543
1600/3021 [==============>...............] - ETA: 0s - loss: 0.1029 - mse: 0.1029
3021/3021 [==============================] - 1s 174us/sample - loss: 0.1014 - mse: 0.1014 - val_loss: 0.0509 - val_mse: 0.0509
Epoch 43/50
100/3021 [..............................] - ETA: 0s - loss: 0.0911 - mse: 0.0911
1600/3021 [==============>...............] - ETA: 0s - loss: 0.1004 - mse: 0.1004
3021/3021 [==============================] - 1s 176us/sample - loss: 0.0996 - mse: 0.0996 - val_loss: 0.0491 - val_mse: 0.0491
Epoch 44/50
100/3021 [..............................] - ETA: 0s - loss: 0.1058 - mse: 0.1058
1000/3021 [========>.....................] - ETA: 0s - loss: 0.0969 - mse: 0.0969
2900/3021 [===========================>..] - ETA: 0s - loss: 0.0985 - mse: 0.0985
3021/3021 [==============================] - 1s 170us/sample - loss: 0.0991 - mse: 0.0991 - val_loss: 0.0474 - val_mse: 0.0474
Epoch 45/50
100/3021 [..............................] - ETA: 0s - loss: 0.1311 - mse: 0.1311
1700/3021 [===============>..............] - ETA: 0s - loss: 0.0891 - mse: 0.0891
3021/3021 [==============================] - 1s 183us/sample - loss: 0.0941 - mse: 0.0941 - val_loss: 0.0511 - val_mse: 0.0511
Epoch 46/50
100/3021 [..............................] - ETA: 0s - loss: 0.0983 - mse: 0.0983
1200/3021 [==========>...................] - ETA: 0s - loss: 0.0984 - mse: 0.0984
2600/3021 [========================>.....] - ETA: 0s - loss: 0.0973 - mse: 0.0973
3021/3021 [==============================] - 1s 198us/sample - loss: 0.0966 - mse: 0.0966 - val_loss: 0.0569 - val_mse: 0.0569
Epoch 47/50
100/3021 [..............................] - ETA: 0s - loss: 0.1177 - mse: 0.1177
1600/3021 [==============>...............] - ETA: 0s - loss: 0.1044 - mse: 0.1044
3021/3021 [==============================] - 1s 170us/sample - loss: 0.0985 - mse: 0.0985 - val_loss: 0.0511 - val_mse: 0.0511
Epoch 48/50
100/3021 [..............................] - ETA: 0s - loss: 0.1566 - mse: 0.1566
1600/3021 [==============>...............] - ETA: 0s - loss: 0.0985 - mse: 0.0985
3021/3021 [==============================] - 1s 170us/sample - loss: 0.0946 - mse: 0.0946 - val_loss: 0.0460 - val_mse: 0.0460
Epoch 49/50
100/3021 [..............................] - ETA: 0s - loss: 0.0986 - mse: 0.0986
1500/3021 [=============>................] - ETA: 0s - loss: 0.0873 - mse: 0.0873
3021/3021 [==============================] - 1s 173us/sample - loss: 0.0904 - mse: 0.0904 - val_loss: 0.0423 - val_mse: 0.0423
Epoch 50/50
100/3021 [..............................] - ETA: 0s - loss: 0.1100 - mse: 0.1100
1500/3021 [=============>................] - ETA: 0s - loss: 0.0931 - mse: 0.0931
3000/3021 [============================>.] - ETA: 0s - loss: 0.0929 - mse: 0.0929
3021/3021 [==============================] - 1s 172us/sample - loss: 0.0925 - mse: 0.0925 - val_loss: 0.0404 - val_mse: 0.0404Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-05-04T01-04-27Z
Training run 25/46 (flags = list(128, 392, 0.05, 100, 50, "tanh", "tanh", 0.1, 0.05))
Using run directory runs/2020-05-04T01-04-59Z
> FLAGS <- flags(
+ flag_numeric("nodes1", 128),
+ flag_numeric("nodes2", 128),
+ flag_numeric("batch_size", 100),
+ flag_string("activation1" .... [TRUNCATED]
> model = keras_model_sequential()
> model %>%
+ layer_dense(units=FLAGS$nodes1, activation=FLAGS$activation1, input_shape=dim(efw_train2)[2]) %>%
+ layer_dropout(FLAGS$dropout1) %> .... [TRUNCATED]
> model %>% compile(
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ loss = 'mse',
+ metrics = c('mse')
+ )
> model %>% fit(
+ as.matrix(efw_train2), train2Label,
+ epochs=FLAGS$epochs,
+ batch_size=FLAGS$batch_size,
+ validation_data=list(as.matrix( .... [TRUNCATED]
Train on 3021 samples, validate on 334 samples
Epoch 1/50
100/3021 [..............................] - ETA: 21s - loss: 45.6940 - mse: 45.6940
2500/3021 [=======================>......] - ETA: 0s - loss: 11.8358 - mse: 11.8358
3021/3021 [==============================] - 1s 443us/sample - loss: 9.9145 - mse: 9.9145 - val_loss: 0.6270 - val_mse: 0.6270
Epoch 2/50
100/3021 [..............................] - ETA: 0s - loss: 0.8655 - mse: 0.8655
1400/3021 [============>.................] - ETA: 0s - loss: 0.4734 - mse: 0.4734
2900/3021 [===========================>..] - ETA: 0s - loss: 0.3546 - mse: 0.3546
3021/3021 [==============================] - 1s 208us/sample - loss: 0.3469 - mse: 0.3469 - val_loss: 0.1258 - val_mse: 0.1258
Epoch 3/50
100/3021 [..............................] - ETA: 0s - loss: 0.1963 - mse: 0.1963
1500/3021 [=============>................] - ETA: 0s - loss: 0.1815 - mse: 0.1815
3000/3021 [============================>.] - ETA: 0s - loss: 0.1746 - mse: 0.1746
3021/3021 [==============================] - 1s 185us/sample - loss: 0.1744 - mse: 0.1744 - val_loss: 0.0790 - val_mse: 0.0790
Epoch 4/50
100/3021 [..............................] - ETA: 0s - loss: 0.1149 - mse: 0.1149
2000/3021 [==================>...........] - ETA: 0s - loss: 0.1406 - mse: 0.1406
3021/3021 [==============================] - 0s 165us/sample - loss: 0.1376 - mse: 0.1376 - val_loss: 0.0651 - val_mse: 0.0651
Epoch 5/50
100/3021 [..............................] - ETA: 0s - loss: 0.1195 - mse: 0.1195
2200/3021 [====================>.........] - ETA: 0s - loss: 0.1351 - mse: 0.1351
3021/3021 [==============================] - 1s 175us/sample - loss: 0.1366 - mse: 0.1366 - val_loss: 0.1173 - val_mse: 0.1173
Epoch 6/50
100/3021 [..............................] - ETA: 0s - loss: 0.1722 - mse: 0.1722
2300/3021 [=====================>........] - ETA: 0s - loss: 0.1615 - mse: 0.1615
3021/3021 [==============================] - 0s 155us/sample - loss: 0.1535 - mse: 0.1535 - val_loss: 0.0592 - val_mse: 0.0592
Epoch 7/50
100/3021 [..............................] - ETA: 0s - loss: 0.1409 - mse: 0.1409
2200/3021 [====================>.........] - ETA: 0s - loss: 0.1210 - mse: 0.1210
3021/3021 [==============================] - 1s 178us/sample - loss: 0.1178 - mse: 0.1178 - val_loss: 0.0620 - val_mse: 0.0620
Epoch 8/50
100/3021 [..............................] - ETA: 0s - loss: 0.1234 - mse: 0.1234
1600/3021 [==============>...............] - ETA: 0s - loss: 0.1157 - mse: 0.1157
3021/3021 [==============================] - 0s 155us/sample - loss: 0.1249 - mse: 0.1249 - val_loss: 0.1646 - val_mse: 0.1646
Epoch 9/50
100/3021 [..............................] - ETA: 0s - loss: 0.2301 - mse: 0.2301
2200/3021 [====================>.........] - ETA: 0s - loss: 0.1921 - mse: 0.1921
3021/3021 [==============================] - 0s 158us/sample - loss: 0.1726 - mse: 0.1726 - val_loss: 0.0639 - val_mse: 0.0639
Epoch 10/50
100/3021 [..............................] - ETA: 0s - loss: 0.1231 - mse: 0.1231
2100/3021 [===================>..........] - ETA: 0s - loss: 0.1334 - mse: 0.1334
3021/3021 [==============================] - 0s 163us/sample - loss: 0.1269 - mse: 0.1269 - val_loss: 0.0506 - val_mse: 0.0506
Epoch 11/50
100/3021 [..............................] - ETA: 0s - loss: 0.1195 - mse: 0.1195
1700/3021 [===============>..............] - ETA: 0s - loss: 0.1134 - mse: 0.1134
3021/3021 [==============================] - 1s 174us/sample - loss: 0.1093 - mse: 0.1093 - val_loss: 0.1554 - val_mse: 0.1554
Epoch 12/50
100/3021 [..............................] - ETA: 0s - loss: 0.1823 - mse: 0.1823
1600/3021 [==============>...............] - ETA: 0s - loss: 0.1214 - mse: 0.1214
3021/3021 [==============================] - 1s 178us/sample - loss: 0.1167 - mse: 0.1167 - val_loss: 0.0544 - val_mse: 0.0544
Epoch 13/50
100/3021 [..............................] - ETA: 0s - loss: 0.0838 - mse: 0.0838
2100/3021 [===================>..........] - ETA: 0s - loss: 0.1092 - mse: 0.1092
3021/3021 [==============================] - 1s 175us/sample - loss: 0.1076 - mse: 0.1076 - val_loss: 0.1147 - val_mse: 0.1147
Epoch 14/50
100/3021 [..............................] - ETA: 0s - loss: 0.1323 - mse: 0.1323
2300/3021 [=====================>........] - ETA: 0s - loss: 0.1189 - mse: 0.1189
3021/3021 [==============================] - 0s 162us/sample - loss: 0.1107 - mse: 0.1107 - val_loss: 0.0521 - val_mse: 0.0521
Epoch 15/50
100/3021 [..............................] - ETA: 0s - loss: 0.0919 - mse: 0.0919
2100/3021 [===================>..........] - ETA: 0s - loss: 0.1022 - mse: 0.1022
3021/3021 [==============================] - 1s 167us/sample - loss: 0.1137 - mse: 0.1137 - val_loss: 0.0743 - val_mse: 0.0743
Epoch 16/50
100/3021 [..............................] - ETA: 0s - loss: 0.0953 - mse: 0.0953
2200/3021 [====================>.........] - ETA: 0s - loss: 0.1208 - mse: 0.1208
3021/3021 [==============================] - 0s 156us/sample - loss: 0.1258 - mse: 0.1258 - val_loss: 0.1133 - val_mse: 0.1133
Epoch 17/50
100/3021 [..............................] - ETA: 0s - loss: 0.1558 - mse: 0.1558
2000/3021 [==================>...........] - ETA: 0s - loss: 0.1396 - mse: 0.1396
3021/3021 [==============================] - 0s 164us/sample - loss: 0.1291 - mse: 0.1291 - val_loss: 0.0872 - val_mse: 0.0872
Epoch 18/50
100/3021 [..............................] - ETA: 0s - loss: 0.1517 - mse: 0.1517
1900/3021 [=================>............] - ETA: 0s - loss: 0.1115 - mse: 0.1115
3021/3021 [==============================] - 0s 165us/sample - loss: 0.1065 - mse: 0.1065 - val_loss: 0.0551 - val_mse: 0.0551
Epoch 19/50
100/3021 [..............................] - ETA: 0s - loss: 0.0770 - mse: 0.0770
1900/3021 [=================>............] - ETA: 0s - loss: 0.0915 - mse: 0.0915
3021/3021 [==============================] - 1s 167us/sample - loss: 0.0956 - mse: 0.0956 - val_loss: 0.0728 - val_mse: 0.0728
Epoch 20/50
100/3021 [..............................] - ETA: 0s - loss: 0.1120 - mse: 0.1120
1700/3021 [===============>..............] - ETA: 0s - loss: 0.1167 - mse: 0.1167
3021/3021 [==============================] - 0s 164us/sample - loss: 0.1080 - mse: 0.1080 - val_loss: 0.0567 - val_mse: 0.0567
Epoch 21/50
100/3021 [..............................] - ETA: 0s - loss: 0.0788 - mse: 0.0788
1700/3021 [===============>..............] - ETA: 0s - loss: 0.0884 - mse: 0.0884
3021/3021 [==============================] - 1s 166us/sample - loss: 0.0912 - mse: 0.0912 - val_loss: 0.0826 - val_mse: 0.0826
Epoch 22/50
100/3021 [..............................] - ETA: 0s - loss: 0.1252 - mse: 0.1252
1600/3021 [==============>...............] - ETA: 0s - loss: 0.1061 - mse: 0.1061
3021/3021 [==============================] - 0s 165us/sample - loss: 0.0991 - mse: 0.0991 - val_loss: 0.0518 - val_mse: 0.0518
Epoch 23/50
100/3021 [..............................] - ETA: 0s - loss: 0.0750 - mse: 0.0750
2100/3021 [===================>..........] - ETA: 0s - loss: 0.0847 - mse: 0.0847
3021/3021 [==============================] - 0s 164us/sample - loss: 0.0838 - mse: 0.0838 - val_loss: 0.0618 - val_mse: 0.0618
Epoch 24/50
100/3021 [..............................] - ETA: 0s - loss: 0.0987 - mse: 0.0987
1300/3021 [===========>..................] - ETA: 0s - loss: 0.0913 - mse: 0.0913
3000/3021 [============================>.] - ETA: 0s - loss: 0.0959 - mse: 0.0959
3021/3021 [==============================] - 1s 181us/sample - loss: 0.0958 - mse: 0.0958 - val_loss: 0.1056 - val_mse: 0.1056
Epoch 25/50
100/3021 [..............................] - ETA: 0s - loss: 0.1310 - mse: 0.1310
1900/3021 [=================>............] - ETA: 0s - loss: 0.1160 - mse: 0.1160
3021/3021 [==============================] - 1s 186us/sample - loss: 0.1212 - mse: 0.1212 - val_loss: 0.2670 - val_mse: 0.2670
Epoch 26/50
100/3021 [..............................] - ETA: 0s - loss: 0.2790 - mse: 0.2790
2100/3021 [===================>..........] - ETA: 0s - loss: 0.1350 - mse: 0.1350
3021/3021 [==============================] - 0s 160us/sample - loss: 0.1191 - mse: 0.1191 - val_loss: 0.1073 - val_mse: 0.1073
Epoch 27/50
100/3021 [..............................] - ETA: 0s - loss: 0.1210 - mse: 0.1210
2300/3021 [=====================>........] - ETA: 0s - loss: 0.1183 - mse: 0.1183
3021/3021 [==============================] - 0s 152us/sample - loss: 0.1140 - mse: 0.1140 - val_loss: 0.0830 - val_mse: 0.0830
Epoch 28/50
100/3021 [..............................] - ETA: 0s - loss: 0.1071 - mse: 0.1071
1900/3021 [=================>............] - ETA: 0s - loss: 0.1004 - mse: 0.1004
3000/3021 [============================>.] - ETA: 0s - loss: 0.1016 - mse: 0.1016
3021/3021 [==============================] - 1s 208us/sample - loss: 0.1015 - mse: 0.1015 - val_loss: 0.1564 - val_mse: 0.1564
Epoch 29/50
100/3021 [..............................] - ETA: 0s - loss: 0.1289 - mse: 0.1289
2100/3021 [===================>..........] - ETA: 0s - loss: 0.1519 - mse: 0.1519
3021/3021 [==============================] - 1s 170us/sample - loss: 0.1627 - mse: 0.1627 - val_loss: 0.0892 - val_mse: 0.0892
Epoch 30/50
100/3021 [..............................] - ETA: 0s - loss: 0.1261 - mse: 0.1261
1500/3021 [=============>................] - ETA: 0s - loss: 0.1254 - mse: 0.1254
3021/3021 [==============================] - 0s 162us/sample - loss: 0.1097 - mse: 0.1097 - val_loss: 0.0714 - val_mse: 0.0714
Epoch 31/50
100/3021 [..............................] - ETA: 0s - loss: 0.0793 - mse: 0.0793
2000/3021 [==================>...........] - ETA: 0s - loss: 0.1150 - mse: 0.1150
3021/3021 [==============================] - 0s 156us/sample - loss: 0.1057 - mse: 0.1057 - val_loss: 0.0980 - val_mse: 0.0980
Epoch 32/50
100/3021 [..............................] - ETA: 0s - loss: 0.1370 - mse: 0.1370
2000/3021 [==================>...........] - ETA: 0s - loss: 0.0931 - mse: 0.0931
3021/3021 [==============================] - 0s 158us/sample - loss: 0.0946 - mse: 0.0946 - val_loss: 0.1976 - val_mse: 0.1976
Epoch 33/50
100/3021 [..............................] - ETA: 0s - loss: 0.2354 - mse: 0.2354
1800/3021 [================>.............] - ETA: 0s - loss: 0.1148 - mse: 0.1148
3021/3021 [==============================] - 1s 185us/sample - loss: 0.1106 - mse: 0.1106 - val_loss: 0.0478 - val_mse: 0.0478
Epoch 34/50
100/3021 [..............................] - ETA: 0s - loss: 0.0736 - mse: 0.0736
1600/3021 [==============>...............] - ETA: 0s - loss: 0.1159 - mse: 0.1159
3021/3021 [==============================] - 1s 174us/sample - loss: 0.1709 - mse: 0.1709 - val_loss: 0.1709 - val_mse: 0.1709
Epoch 35/50
100/3021 [..............................] - ETA: 0s - loss: 0.1769 - mse: 0.1769
1200/3021 [==========>...................] - ETA: 0s - loss: 0.1378 - mse: 0.1378
3021/3021 [==============================] - 1s 171us/sample - loss: 0.1108 - mse: 0.1108 - val_loss: 0.0714 - val_mse: 0.0714
Epoch 36/50
100/3021 [..............................] - ETA: 0s - loss: 0.0994 - mse: 0.0994
2100/3021 [===================>..........] - ETA: 0s - loss: 0.0786 - mse: 0.0786
3021/3021 [==============================] - 0s 162us/sample - loss: 0.0760 - mse: 0.0760 - val_loss: 0.0390 - val_mse: 0.0390
Epoch 37/50
100/3021 [..............................] - ETA: 0s - loss: 0.0535 - mse: 0.0535
1600/3021 [==============>...............] - ETA: 0s - loss: 0.0757 - mse: 0.0757
2900/3021 [===========================>..] - ETA: 0s - loss: 0.0771 - mse: 0.0771
3021/3021 [==============================] - 1s 184us/sample - loss: 0.0768 - mse: 0.0768 - val_loss: 0.0752 - val_mse: 0.0752
Epoch 38/50
100/3021 [..............................] - ETA: 0s - loss: 0.1036 - mse: 0.1036
2300/3021 [=====================>........] - ETA: 0s - loss: 0.0794 - mse: 0.0794
3021/3021 [==============================] - 1s 171us/sample - loss: 0.0788 - mse: 0.0788 - val_loss: 0.0622 - val_mse: 0.0622
Epoch 39/50
100/3021 [..............................] - ETA: 0s - loss: 0.0795 - mse: 0.0795
1200/3021 [==========>...................] - ETA: 0s - loss: 0.0701 - mse: 0.0701
3021/3021 [==============================] - 1s 166us/sample - loss: 0.0737 - mse: 0.0737 - val_loss: 0.1125 - val_mse: 0.1125
Epoch 40/50
100/3021 [..............................] - ETA: 0s - loss: 0.1392 - mse: 0.1392
1800/3021 [================>.............] - ETA: 0s - loss: 0.0988 - mse: 0.0988
3021/3021 [==============================] - 1s 169us/sample - loss: 0.0912 - mse: 0.0912 - val_loss: 0.0589 - val_mse: 0.0589
Epoch 41/50
100/3021 [..............................] - ETA: 0s - loss: 0.0551 - mse: 0.0551
2000/3021 [==================>...........] - ETA: 0s - loss: 0.0737 - mse: 0.0737
3021/3021 [==============================] - 0s 154us/sample - loss: 0.0740 - mse: 0.0740 - val_loss: 0.0552 - val_mse: 0.0552
Epoch 42/50
100/3021 [..............................] - ETA: 0s - loss: 0.0727 - mse: 0.0727
2100/3021 [===================>..........] - ETA: 0s - loss: 0.0669 - mse: 0.0669
3021/3021 [==============================] - 0s 158us/sample - loss: 0.0648 - mse: 0.0648 - val_loss: 0.0717 - val_mse: 0.0717
Epoch 43/50
100/3021 [..............................] - ETA: 0s - loss: 0.0758 - mse: 0.0758
2100/3021 [===================>..........] - ETA: 0s - loss: 0.1139 - mse: 0.1139
3021/3021 [==============================] - 1s 166us/sample - loss: 0.1173 - mse: 0.1173 - val_loss: 0.0936 - val_mse: 0.0936
Epoch 44/50
100/3021 [..............................] - ETA: 0s - loss: 0.1146 - mse: 0.1146
1400/3021 [============>.................] - ETA: 0s - loss: 0.0934 - mse: 0.0934
3021/3021 [==============================] - 1s 181us/sample - loss: 0.0831 - mse: 0.0831 - val_loss: 0.0640 - val_mse: 0.0640
Epoch 45/50
100/3021 [..............................] - ETA: 0s - loss: 0.0707 - mse: 0.0707
1500/3021 [=============>................] - ETA: 0s - loss: 0.0967 - mse: 0.0967
2900/3021 [===========================>..] - ETA: 0s - loss: 0.1028 - mse: 0.1028
3021/3021 [==============================] - 1s 212us/sample - loss: 0.1030 - mse: 0.1030 - val_loss: 0.0798 - val_mse: 0.0798
Epoch 46/50
100/3021 [..............................] - ETA: 0s - loss: 0.0764 - mse: 0.0764
2000/3021 [==================>...........] - ETA: 0s - loss: 0.0816 - mse: 0.0816
3021/3021 [==============================] - 1s 173us/sample - loss: 0.0805 - mse: 0.0805 - val_loss: 0.1201 - val_mse: 0.1201
Epoch 47/50
100/3021 [..............................] - ETA: 0s - loss: 0.1278 - mse: 0.1278
1500/3021 [=============>................] - ETA: 0s - loss: 0.0842 - mse: 0.0842
3021/3021 [==============================] - 0s 165us/sample - loss: 0.0763 - mse: 0.0763 - val_loss: 0.0639 - val_mse: 0.0639
Epoch 48/50
100/3021 [..............................] - ETA: 0s - loss: 0.0732 - mse: 0.0732
2300/3021 [=====================>........] - ETA: 0s - loss: 0.0708 - mse: 0.0708
3021/3021 [==============================] - 0s 155us/sample - loss: 0.0702 - mse: 0.0702 - val_loss: 0.0672 - val_mse: 0.0672
Epoch 49/50
100/3021 [..............................] - ETA: 0s - loss: 0.0687 - mse: 0.0687
1800/3021 [================>.............] - ETA: 0s - loss: 0.0727 - mse: 0.0727
3021/3021 [==============================] - 1s 183us/sample - loss: 0.0686 - mse: 0.0686 - val_loss: 0.0498 - val_mse: 0.0498
Epoch 50/50
100/3021 [..............................] - ETA: 0s - loss: 0.0423 - mse: 0.0423
2100/3021 [===================>..........] - ETA: 0s - loss: 0.0665 - mse: 0.0665
3021/3021 [==============================] - 1s 166us/sample - loss: 0.0712 - mse: 0.0712 - val_loss: 0.0809 - val_mse: 0.0809Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-05-04T01-04-59Z
Training run 26/46 (flags = list(64, 64, 1e-04, 100, 50, "tanh", "tanh", 0.2, 0.5))
Using run directory runs/2020-05-04T01-05-29Z
> FLAGS <- flags(
+ flag_numeric("nodes1", 128),
+ flag_numeric("nodes2", 128),
+ flag_numeric("batch_size", 100),
+ flag_string("activation1" .... [TRUNCATED]
> model = keras_model_sequential()
> model %>%
+ layer_dense(units=FLAGS$nodes1, activation=FLAGS$activation1, input_shape=dim(efw_train2)[2]) %>%
+ layer_dropout(FLAGS$dropout1) %> .... [TRUNCATED]
> model %>% compile(
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ loss = 'mse',
+ metrics = c('mse')
+ )
> model %>% fit(
+ as.matrix(efw_train2), train2Label,
+ epochs=FLAGS$epochs,
+ batch_size=FLAGS$batch_size,
+ validation_data=list(as.matrix( .... [TRUNCATED]
Train on 3021 samples, validate on 334 samples
Epoch 1/50
100/3021 [..............................] - ETA: 8s - loss: 44.1924 - mse: 44.1924
2300/3021 [=====================>........] - ETA: 0s - loss: 43.3217 - mse: 43.3217
3021/3021 [==============================] - 1s 298us/sample - loss: 43.3046 - mse: 43.3046 - val_loss: 42.5823 - val_mse: 42.5823
Epoch 2/50
100/3021 [..............................] - ETA: 0s - loss: 41.6929 - mse: 41.6929
1800/3021 [================>.............] - ETA: 0s - loss: 42.2639 - mse: 42.2639
3021/3021 [==============================] - 1s 178us/sample - loss: 42.0495 - mse: 42.0495 - val_loss: 41.5646 - val_mse: 41.5646
Epoch 3/50
100/3021 [..............................] - ETA: 0s - loss: 40.6417 - mse: 40.6417
2100/3021 [===================>..........] - ETA: 0s - loss: 41.3201 - mse: 41.3201
3021/3021 [==============================] - 1s 168us/sample - loss: 41.1402 - mse: 41.1402 - val_loss: 40.6496 - val_mse: 40.6496
Epoch 4/50
100/3021 [..............................] - ETA: 0s - loss: 40.4464 - mse: 40.4464
1100/3021 [=========>....................] - ETA: 0s - loss: 40.6158 - mse: 40.6158
3021/3021 [==============================] - 0s 159us/sample - loss: 40.1053 - mse: 40.1053 - val_loss: 39.7671 - val_mse: 39.7671
Epoch 5/50
100/3021 [..............................] - ETA: 0s - loss: 39.7947 - mse: 39.7947
2000/3021 [==================>...........] - ETA: 0s - loss: 39.5689 - mse: 39.5689
3021/3021 [==============================] - 1s 199us/sample - loss: 39.2875 - mse: 39.2875 - val_loss: 38.8958 - val_mse: 38.8958
Epoch 6/50
100/3021 [..............................] - ETA: 0s - loss: 39.7716 - mse: 39.7716
1900/3021 [=================>............] - ETA: 0s - loss: 38.6703 - mse: 38.6703
3021/3021 [==============================] - 1s 183us/sample - loss: 38.3305 - mse: 38.3305 - val_loss: 38.0226 - val_mse: 38.0226
Epoch 7/50
100/3021 [..............................] - ETA: 0s - loss: 37.4062 - mse: 37.4062
1900/3021 [=================>............] - ETA: 0s - loss: 37.4334 - mse: 37.4334
3021/3021 [==============================] - 1s 184us/sample - loss: 37.3506 - mse: 37.3506 - val_loss: 37.1224 - val_mse: 37.1224
Epoch 8/50
100/3021 [..............................] - ETA: 0s - loss: 36.4629 - mse: 36.4629
1100/3021 [=========>....................] - ETA: 0s - loss: 36.6886 - mse: 36.6886
3021/3021 [==============================] - 1s 167us/sample - loss: 36.4551 - mse: 36.4551 - val_loss: 36.2294 - val_mse: 36.2294
Epoch 9/50
100/3021 [..............................] - ETA: 0s - loss: 36.4607 - mse: 36.4607
1400/3021 [============>.................] - ETA: 0s - loss: 35.9917 - mse: 35.9917
3021/3021 [==============================] - 0s 155us/sample - loss: 35.5543 - mse: 35.5543 - val_loss: 35.3143 - val_mse: 35.3143
Epoch 10/50
100/3021 [..............................] - ETA: 0s - loss: 35.0065 - mse: 35.0065
2700/3021 [=========================>....] - ETA: 0s - loss: 34.6666 - mse: 34.6666
3021/3021 [==============================] - 0s 148us/sample - loss: 34.5831 - mse: 34.5831 - val_loss: 34.3681 - val_mse: 34.3681
Epoch 11/50
100/3021 [..............................] - ETA: 0s - loss: 34.5157 - mse: 34.5157
1900/3021 [=================>............] - ETA: 0s - loss: 33.8897 - mse: 33.8897
3021/3021 [==============================] - 0s 163us/sample - loss: 33.7032 - mse: 33.7032 - val_loss: 33.4093 - val_mse: 33.4093
Epoch 12/50
100/3021 [..............................] - ETA: 0s - loss: 33.2412 - mse: 33.2412
1500/3021 [=============>................] - ETA: 0s - loss: 33.0585 - mse: 33.0585
3021/3021 [==============================] - 0s 162us/sample - loss: 32.6105 - mse: 32.6105 - val_loss: 32.4293 - val_mse: 32.4293
Epoch 13/50
100/3021 [..............................] - ETA: 0s - loss: 31.8674 - mse: 31.8674
2300/3021 [=====================>........] - ETA: 0s - loss: 31.7907 - mse: 31.7907
3021/3021 [==============================] - 1s 166us/sample - loss: 31.6306 - mse: 31.6306 - val_loss: 31.3943 - val_mse: 31.3943
Epoch 14/50
100/3021 [..............................] - ETA: 0s - loss: 31.0807 - mse: 31.0807
1900/3021 [=================>............] - ETA: 0s - loss: 30.8242 - mse: 30.8242
3021/3021 [==============================] - 1s 189us/sample - loss: 30.6338 - mse: 30.6338 - val_loss: 30.4055 - val_mse: 30.4055
Epoch 15/50
100/3021 [..............................] - ETA: 0s - loss: 30.2371 - mse: 30.2371
1600/3021 [==============>...............] - ETA: 0s - loss: 29.6299 - mse: 29.6299
3021/3021 [==============================] - 1s 189us/sample - loss: 29.4202 - mse: 29.4202 - val_loss: 29.3564 - val_mse: 29.3564
Epoch 16/50
100/3021 [..............................] - ETA: 0s - loss: 28.1861 - mse: 28.1861
2600/3021 [========================>.....] - ETA: 0s - loss: 28.4930 - mse: 28.4930
3021/3021 [==============================] - 1s 179us/sample - loss: 28.4237 - mse: 28.4237 - val_loss: 28.2968 - val_mse: 28.2968
Epoch 17/50
100/3021 [..............................] - ETA: 0s - loss: 27.8453 - mse: 27.8453
2000/3021 [==================>...........] - ETA: 0s - loss: 27.5869 - mse: 27.5869
3021/3021 [==============================] - 1s 193us/sample - loss: 27.3612 - mse: 27.3612 - val_loss: 27.2170 - val_mse: 27.2170
Epoch 18/50
100/3021 [..............................] - ETA: 0s - loss: 26.6065 - mse: 26.6065
2000/3021 [==================>...........] - ETA: 0s - loss: 26.3975 - mse: 26.3975
3021/3021 [==============================] - 0s 165us/sample - loss: 26.1954 - mse: 26.1954 - val_loss: 26.1231 - val_mse: 26.1231
Epoch 19/50
100/3021 [..............................] - ETA: 0s - loss: 25.1762 - mse: 25.1762
1800/3021 [================>.............] - ETA: 0s - loss: 25.2595 - mse: 25.2595
3021/3021 [==============================] - 0s 150us/sample - loss: 25.0570 - mse: 25.0570 - val_loss: 25.0157 - val_mse: 25.0157
Epoch 20/50
100/3021 [..............................] - ETA: 0s - loss: 24.2446 - mse: 24.2446
2400/3021 [======================>.......] - ETA: 0s - loss: 24.3485 - mse: 24.3485
3021/3021 [==============================] - 1s 167us/sample - loss: 24.1759 - mse: 24.1759 - val_loss: 23.9235 - val_mse: 23.9235
Epoch 21/50
100/3021 [..............................] - ETA: 0s - loss: 23.0270 - mse: 23.0270
1800/3021 [================>.............] - ETA: 0s - loss: 23.2044 - mse: 23.2044
3021/3021 [==============================] - 1s 205us/sample - loss: 22.9139 - mse: 22.9139 - val_loss: 22.8278 - val_mse: 22.8278
Epoch 22/50
100/3021 [..............................] - ETA: 0s - loss: 23.0006 - mse: 23.0006
1800/3021 [================>.............] - ETA: 0s - loss: 22.0912 - mse: 22.0912
3021/3021 [==============================] - 1s 176us/sample - loss: 21.8228 - mse: 21.8228 - val_loss: 21.7603 - val_mse: 21.7603
Epoch 23/50
100/3021 [..............................] - ETA: 0s - loss: 21.2224 - mse: 21.2224
2700/3021 [=========================>....] - ETA: 0s - loss: 20.7325 - mse: 20.7325
3021/3021 [==============================] - 0s 160us/sample - loss: 20.6564 - mse: 20.6564 - val_loss: 20.6434 - val_mse: 20.6434
Epoch 24/50
100/3021 [..............................] - ETA: 0s - loss: 19.9684 - mse: 19.9684
1500/3021 [=============>................] - ETA: 0s - loss: 19.8379 - mse: 19.8379
2900/3021 [===========================>..] - ETA: 0s - loss: 19.5476 - mse: 19.5476
3021/3021 [==============================] - 1s 197us/sample - loss: 19.5570 - mse: 19.5570 - val_loss: 19.5737 - val_mse: 19.5737
Epoch 25/50
100/3021 [..............................] - ETA: 0s - loss: 19.1152 - mse: 19.1152
1900/3021 [=================>............] - ETA: 0s - loss: 18.8087 - mse: 18.8087
3021/3021 [==============================] - 1s 171us/sample - loss: 18.5510 - mse: 18.5510 - val_loss: 18.5175 - val_mse: 18.5175
Epoch 26/50
100/3021 [..............................] - ETA: 0s - loss: 18.4272 - mse: 18.4272
1800/3021 [================>.............] - ETA: 0s - loss: 17.8494 - mse: 17.8494
3021/3021 [==============================] - 1s 182us/sample - loss: 17.5266 - mse: 17.5266 - val_loss: 17.4411 - val_mse: 17.4411
Epoch 27/50
100/3021 [..............................] - ETA: 0s - loss: 16.6593 - mse: 16.6593
2200/3021 [====================>.........] - ETA: 0s - loss: 16.6352 - mse: 16.6352
3021/3021 [==============================] - 0s 162us/sample - loss: 16.4029 - mse: 16.4029 - val_loss: 16.4104 - val_mse: 16.4104
Epoch 28/50
100/3021 [..............................] - ETA: 0s - loss: 15.6943 - mse: 15.6943
2000/3021 [==================>...........] - ETA: 0s - loss: 15.6992 - mse: 15.6992
3021/3021 [==============================] - 1s 185us/sample - loss: 15.3518 - mse: 15.3518 - val_loss: 15.3926 - val_mse: 15.3926
Epoch 29/50
100/3021 [..............................] - ETA: 0s - loss: 14.7821 - mse: 14.7821
2500/3021 [=======================>......] - ETA: 0s - loss: 14.4812 - mse: 14.4812
3021/3021 [==============================] - 0s 156us/sample - loss: 14.3957 - mse: 14.3957 - val_loss: 14.4152 - val_mse: 14.4152
Epoch 30/50
100/3021 [..............................] - ETA: 0s - loss: 14.1147 - mse: 14.1147
2600/3021 [========================>.....] - ETA: 0s - loss: 13.4355 - mse: 13.4355
3021/3021 [==============================] - 0s 153us/sample - loss: 13.4124 - mse: 13.4124 - val_loss: 13.4694 - val_mse: 13.4694
Epoch 31/50
100/3021 [..............................] - ETA: 0s - loss: 12.4852 - mse: 12.4852
2200/3021 [====================>.........] - ETA: 0s - loss: 12.6964 - mse: 12.6964
3021/3021 [==============================] - 0s 147us/sample - loss: 12.5187 - mse: 12.5187 - val_loss: 12.5311 - val_mse: 12.5311
Epoch 32/50
100/3021 [..............................] - ETA: 0s - loss: 12.3639 - mse: 12.3639
2600/3021 [========================>.....] - ETA: 0s - loss: 11.6187 - mse: 11.6187
3021/3021 [==============================] - 0s 151us/sample - loss: 11.5733 - mse: 11.5733 - val_loss: 11.6449 - val_mse: 11.6449
Epoch 33/50
100/3021 [..............................] - ETA: 0s - loss: 11.5686 - mse: 11.5686
1300/3021 [===========>..................] - ETA: 0s - loss: 11.0679 - mse: 11.0679
3021/3021 [==============================] - 1s 169us/sample - loss: 10.7046 - mse: 10.7046 - val_loss: 10.8015 - val_mse: 10.8015
Epoch 34/50
100/3021 [..............................] - ETA: 0s - loss: 9.8636 - mse: 9.8636
2200/3021 [====================>.........] - ETA: 0s - loss: 10.0728 - mse: 10.0728
3021/3021 [==============================] - 0s 159us/sample - loss: 9.9859 - mse: 9.9859 - val_loss: 9.9814 - val_mse: 9.9814
Epoch 35/50
100/3021 [..............................] - ETA: 0s - loss: 9.0455 - mse: 9.0455
1300/3021 [===========>..................] - ETA: 0s - loss: 9.3665 - mse: 9.3665
3021/3021 [==============================] - 0s 154us/sample - loss: 9.1905 - mse: 9.1905 - val_loss: 9.1784 - val_mse: 9.1784
Epoch 36/50
100/3021 [..............................] - ETA: 0s - loss: 8.5655 - mse: 8.5655
2800/3021 [==========================>...] - ETA: 0s - loss: 8.4560 - mse: 8.4560
3021/3021 [==============================] - 0s 152us/sample - loss: 8.4227 - mse: 8.4227 - val_loss: 8.4264 - val_mse: 8.4264
Epoch 37/50
100/3021 [..............................] - ETA: 0s - loss: 8.0945 - mse: 8.0945
2300/3021 [=====================>........] - ETA: 0s - loss: 7.7139 - mse: 7.7139
3021/3021 [==============================] - 0s 159us/sample - loss: 7.6542 - mse: 7.6542 - val_loss: 7.7170 - val_mse: 7.7170
Epoch 38/50
100/3021 [..............................] - ETA: 0s - loss: 7.7586 - mse: 7.7586
1900/3021 [=================>............] - ETA: 0s - loss: 7.1970 - mse: 7.1970
3021/3021 [==============================] - 1s 189us/sample - loss: 7.0397 - mse: 7.0397 - val_loss: 7.0482 - val_mse: 7.0482
Epoch 39/50
100/3021 [..............................] - ETA: 0s - loss: 6.8761 - mse: 6.8761
1500/3021 [=============>................] - ETA: 0s - loss: 6.5403 - mse: 6.5403
3021/3021 [==============================] - 1s 180us/sample - loss: 6.4457 - mse: 6.4457 - val_loss: 6.4156 - val_mse: 6.4156
Epoch 40/50
100/3021 [..............................] - ETA: 0s - loss: 5.8251 - mse: 5.8251
1700/3021 [===============>..............] - ETA: 0s - loss: 5.8826 - mse: 5.8826
3021/3021 [==============================] - 1s 200us/sample - loss: 5.8456 - mse: 5.8456 - val_loss: 5.8178 - val_mse: 5.8178
Epoch 41/50
100/3021 [..............................] - ETA: 0s - loss: 5.5662 - mse: 5.5662
2500/3021 [=======================>......] - ETA: 0s - loss: 5.3328 - mse: 5.3328
3021/3021 [==============================] - 0s 161us/sample - loss: 5.2765 - mse: 5.2765 - val_loss: 5.2600 - val_mse: 5.2600
Epoch 42/50
100/3021 [..............................] - ETA: 0s - loss: 5.4331 - mse: 5.4331
2000/3021 [==================>...........] - ETA: 0s - loss: 4.8097 - mse: 4.8097
3021/3021 [==============================] - 0s 160us/sample - loss: 4.7219 - mse: 4.7219 - val_loss: 4.7474 - val_mse: 4.7474
Epoch 43/50
100/3021 [..............................] - ETA: 0s - loss: 4.3974 - mse: 4.3974
2200/3021 [====================>.........] - ETA: 0s - loss: 4.3255 - mse: 4.3255
3021/3021 [==============================] - 0s 158us/sample - loss: 4.2863 - mse: 4.2863 - val_loss: 4.2753 - val_mse: 4.2753
Epoch 44/50
100/3021 [..............................] - ETA: 0s - loss: 3.8329 - mse: 3.8329
2600/3021 [========================>.....] - ETA: 0s - loss: 3.9137 - mse: 3.9137
3021/3021 [==============================] - 0s 152us/sample - loss: 3.8621 - mse: 3.8621 - val_loss: 3.8356 - val_mse: 3.8356
Epoch 45/50
100/3021 [..............................] - ETA: 0s - loss: 3.6385 - mse: 3.6385
1200/3021 [==========>...................] - ETA: 0s - loss: 3.6760 - mse: 3.6760
3021/3021 [==============================] - 0s 158us/sample - loss: 3.4742 - mse: 3.4742 - val_loss: 3.4306 - val_mse: 3.4306
Epoch 46/50
100/3021 [..............................] - ETA: 0s - loss: 3.4700 - mse: 3.4700
2100/3021 [===================>..........] - ETA: 0s - loss: 3.2384 - mse: 3.2384
3021/3021 [==============================] - 1s 174us/sample - loss: 3.1655 - mse: 3.1655 - val_loss: 3.0549 - val_mse: 3.0549
Epoch 47/50
100/3021 [..............................] - ETA: 0s - loss: 2.6010 - mse: 2.6010
2500/3021 [=======================>......] - ETA: 0s - loss: 2.7889 - mse: 2.7889
3021/3021 [==============================] - 0s 162us/sample - loss: 2.7805 - mse: 2.7805 - val_loss: 2.7166 - val_mse: 2.7166
Epoch 48/50
100/3021 [..............................] - ETA: 0s - loss: 2.6524 - mse: 2.6524
2600/3021 [========================>.....] - ETA: 0s - loss: 2.5031 - mse: 2.5031
3021/3021 [==============================] - 0s 162us/sample - loss: 2.4908 - mse: 2.4908 - val_loss: 2.4069 - val_mse: 2.4069
Epoch 49/50
100/3021 [..............................] - ETA: 0s - loss: 2.2938 - mse: 2.2938
1500/3021 [=============>................] - ETA: 0s - loss: 2.3006 - mse: 2.3006
3000/3021 [============================>.] - ETA: 0s - loss: 2.1816 - mse: 2.1816
3021/3021 [==============================] - 1s 204us/sample - loss: 2.1821 - mse: 2.1821 - val_loss: 2.1298 - val_mse: 2.1298
Epoch 50/50
100/3021 [..............................] - ETA: 0s - loss: 2.1782 - mse: 2.1782
2300/3021 [=====================>........] - ETA: 0s - loss: 1.9928 - mse: 1.9928
3021/3021 [==============================] - 1s 169us/sample - loss: 1.9804 - mse: 1.9804 - val_loss: 1.8782 - val_mse: 1.8782Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-05-04T01-05-29Z
Training run 27/46 (flags = list(128, 128, 0.05, 500, 30, "relu", "tanh", 0.5, 0.05))
Using run directory runs/2020-05-04T01-05-59Z
> FLAGS <- flags(
+ flag_numeric("nodes1", 128),
+ flag_numeric("nodes2", 128),
+ flag_numeric("batch_size", 100),
+ flag_string("activation1" .... [TRUNCATED]
> model = keras_model_sequential()
> model %>%
+ layer_dense(units=FLAGS$nodes1, activation=FLAGS$activation1, input_shape=dim(efw_train2)[2]) %>%
+ layer_dropout(FLAGS$dropout1) %> .... [TRUNCATED]
> model %>% compile(
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ loss = 'mse',
+ metrics = c('mse')
+ )
> model %>% fit(
+ as.matrix(efw_train2), train2Label,
+ epochs=FLAGS$epochs,
+ batch_size=FLAGS$batch_size,
+ validation_data=list(as.matrix( .... [TRUNCATED]
Train on 3021 samples, validate on 334 samples
Epoch 1/30
500/3021 [===>..........................] - ETA: 1s - loss: 43.7785 - mse: 43.7785
3021/3021 [==============================] - 1s 279us/sample - loss: 22.2048 - mse: 22.2048 - val_loss: 1.8454 - val_mse: 1.8454
Epoch 2/30
500/3021 [===>..........................] - ETA: 0s - loss: 4.3227 - mse: 4.3227
3021/3021 [==============================] - 1s 166us/sample - loss: 5.5457 - mse: 5.5457 - val_loss: 3.2389 - val_mse: 3.2389
Epoch 3/30
500/3021 [===>..........................] - ETA: 0s - loss: 4.7015 - mse: 4.7015
3021/3021 [==============================] - 1s 172us/sample - loss: 3.6831 - mse: 3.6831 - val_loss: 1.4152 - val_mse: 1.4152
Epoch 4/30
500/3021 [===>..........................] - ETA: 0s - loss: 2.3826 - mse: 2.3826
3021/3021 [==============================] - 0s 160us/sample - loss: 2.4170 - mse: 2.4170 - val_loss: 0.8763 - val_mse: 0.8763
Epoch 5/30
500/3021 [===>..........................] - ETA: 0s - loss: 2.2515 - mse: 2.2515
3021/3021 [==============================] - 1s 166us/sample - loss: 1.9374 - mse: 1.9374 - val_loss: 0.5546 - val_mse: 0.5546
Epoch 6/30
500/3021 [===>..........................] - ETA: 0s - loss: 1.6615 - mse: 1.6615
3021/3021 [==============================] - 0s 153us/sample - loss: 1.6549 - mse: 1.6549 - val_loss: 0.9269 - val_mse: 0.9269
Epoch 7/30
500/3021 [===>..........................] - ETA: 0s - loss: 1.6741 - mse: 1.6741
3021/3021 [==============================] - 0s 152us/sample - loss: 1.4792 - mse: 1.4792 - val_loss: 0.4242 - val_mse: 0.4242
Epoch 8/30
500/3021 [===>..........................] - ETA: 0s - loss: 1.3088 - mse: 1.3088
3021/3021 [==============================] - 0s 142us/sample - loss: 1.2386 - mse: 1.2386 - val_loss: 0.3759 - val_mse: 0.3759
Epoch 9/30
500/3021 [===>..........................] - ETA: 0s - loss: 1.2104 - mse: 1.2104
3021/3021 [==============================] - 0s 161us/sample - loss: 1.1572 - mse: 1.1572 - val_loss: 0.2860 - val_mse: 0.2860
Epoch 10/30
500/3021 [===>..........................] - ETA: 0s - loss: 1.0109 - mse: 1.0109
3021/3021 [==============================] - 0s 164us/sample - loss: 0.9985 - mse: 0.9985 - val_loss: 0.2968 - val_mse: 0.2968
Epoch 11/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.9507 - mse: 0.9507
3021/3021 [==============================] - 1s 180us/sample - loss: 0.9400 - mse: 0.9400 - val_loss: 0.3068 - val_mse: 0.3068
Epoch 12/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.9079 - mse: 0.9079
3021/3021 [==============================] - 0s 148us/sample - loss: 0.9848 - mse: 0.9848 - val_loss: 0.3076 - val_mse: 0.3076
Epoch 13/30
500/3021 [===>..........................] - ETA: 0s - loss: 1.0003 - mse: 1.0003
3021/3021 [==============================] - 0s 146us/sample - loss: 0.9174 - mse: 0.9174 - val_loss: 0.3037 - val_mse: 0.3037
Epoch 14/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.8861 - mse: 0.8861
3021/3021 [==============================] - 0s 153us/sample - loss: 0.9091 - mse: 0.9091 - val_loss: 0.2707 - val_mse: 0.2707
Epoch 15/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.8834 - mse: 0.8834
3021/3021 [==============================] - 0s 149us/sample - loss: 0.8596 - mse: 0.8596 - val_loss: 0.2792 - val_mse: 0.2792
Epoch 16/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.8517 - mse: 0.8517
3021/3021 [==============================] - 0s 146us/sample - loss: 0.8618 - mse: 0.8618 - val_loss: 0.2560 - val_mse: 0.2560
Epoch 17/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.9546 - mse: 0.9546
3021/3021 [==============================] - 0s 137us/sample - loss: 0.9032 - mse: 0.9032 - val_loss: 0.2212 - val_mse: 0.2212
Epoch 18/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.7787 - mse: 0.7787
3021/3021 [==============================] - 0s 134us/sample - loss: 0.7742 - mse: 0.7742 - val_loss: 0.1948 - val_mse: 0.1948
Epoch 19/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.7738 - mse: 0.7738
3021/3021 [==============================] - 0s 138us/sample - loss: 0.7451 - mse: 0.7451 - val_loss: 0.2832 - val_mse: 0.2832
Epoch 20/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.7982 - mse: 0.7982
3021/3021 [==============================] - 0s 136us/sample - loss: 0.8049 - mse: 0.8049 - val_loss: 0.1804 - val_mse: 0.1804
Epoch 21/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.7956 - mse: 0.7956
3021/3021 [==============================] - 0s 133us/sample - loss: 0.8395 - mse: 0.8395 - val_loss: 0.3107 - val_mse: 0.3107
Epoch 22/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.7882 - mse: 0.7882
3021/3021 [==============================] - 0s 134us/sample - loss: 0.7369 - mse: 0.7369 - val_loss: 0.2325 - val_mse: 0.2325
Epoch 23/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.6668 - mse: 0.6668
3021/3021 [==============================] - 0s 142us/sample - loss: 0.7162 - mse: 0.7162 - val_loss: 0.1915 - val_mse: 0.1915
Epoch 24/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.6205 - mse: 0.6205
3021/3021 [==============================] - 0s 145us/sample - loss: 0.6737 - mse: 0.6737 - val_loss: 0.1808 - val_mse: 0.1808
Epoch 25/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.6539 - mse: 0.6539
3021/3021 [==============================] - 0s 130us/sample - loss: 0.6221 - mse: 0.6221 - val_loss: 0.1466 - val_mse: 0.1466
Epoch 26/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.5960 - mse: 0.5960
3021/3021 [==============================] - 0s 145us/sample - loss: 0.6414 - mse: 0.6414 - val_loss: 0.2057 - val_mse: 0.2057
Epoch 27/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.6266 - mse: 0.6266
3021/3021 [==============================] - 0s 140us/sample - loss: 0.6293 - mse: 0.6293 - val_loss: 0.4939 - val_mse: 0.4939
Epoch 28/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.8785 - mse: 0.8785
3021/3021 [==============================] - 0s 128us/sample - loss: 0.7517 - mse: 0.7517 - val_loss: 0.1518 - val_mse: 0.1518
Epoch 29/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.5519 - mse: 0.5519
3021/3021 [==============================] - 0s 132us/sample - loss: 0.6993 - mse: 0.6993 - val_loss: 0.3823 - val_mse: 0.3823
Epoch 30/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.8833 - mse: 0.8833
3021/3021 [==============================] - 0s 142us/sample - loss: 0.7817 - mse: 0.7817 - val_loss: 0.2132 - val_mse: 0.2132Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-05-04T01-05-59Z
Training run 28/46 (flags = list(128, 128, 0.05, 500, 50, "relu", "relu", 0.5, 0.5))
Using run directory runs/2020-05-04T01-06-17Z
> FLAGS <- flags(
+ flag_numeric("nodes1", 128),
+ flag_numeric("nodes2", 128),
+ flag_numeric("batch_size", 100),
+ flag_string("activation1" .... [TRUNCATED]
> model = keras_model_sequential()
> model %>%
+ layer_dense(units=FLAGS$nodes1, activation=FLAGS$activation1, input_shape=dim(efw_train2)[2]) %>%
+ layer_dropout(FLAGS$dropout1) %> .... [TRUNCATED]
> model %>% compile(
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ loss = 'mse',
+ metrics = c('mse')
+ )
> model %>% fit(
+ as.matrix(efw_train2), train2Label,
+ epochs=FLAGS$epochs,
+ batch_size=FLAGS$batch_size,
+ validation_data=list(as.matrix( .... [TRUNCATED]
Train on 3021 samples, validate on 334 samples
Epoch 1/50
500/3021 [===>..........................] - ETA: 1s - loss: 46.6142 - mse: 46.6142
3021/3021 [==============================] - 1s 273us/sample - loss: 20.1268 - mse: 20.1268 - val_loss: 6.0973 - val_mse: 6.0973
Epoch 2/50
500/3021 [===>..........................] - ETA: 0s - loss: 8.0811 - mse: 8.0811
3021/3021 [==============================] - 0s 145us/sample - loss: 5.6595 - mse: 5.6595 - val_loss: 1.7745 - val_mse: 1.7745
Epoch 3/50
500/3021 [===>..........................] - ETA: 0s - loss: 3.6843 - mse: 3.6843
3021/3021 [==============================] - 0s 155us/sample - loss: 2.8302 - mse: 2.8302 - val_loss: 0.9801 - val_mse: 0.9801
Epoch 4/50
500/3021 [===>..........................] - ETA: 0s - loss: 2.0290 - mse: 2.0290
3021/3021 [==============================] - 0s 140us/sample - loss: 1.9338 - mse: 1.9338 - val_loss: 0.6689 - val_mse: 0.6689
Epoch 5/50
500/3021 [===>..........................] - ETA: 0s - loss: 1.6225 - mse: 1.6225
3021/3021 [==============================] - 0s 149us/sample - loss: 1.6207 - mse: 1.6207 - val_loss: 1.1140 - val_mse: 1.1140
Epoch 6/50
500/3021 [===>..........................] - ETA: 0s - loss: 1.8734 - mse: 1.8734
3021/3021 [==============================] - 1s 272us/sample - loss: 1.6046 - mse: 1.6046 - val_loss: 1.0303 - val_mse: 1.0303
Epoch 7/50
500/3021 [===>..........................] - ETA: 0s - loss: 1.7522 - mse: 1.7522
3021/3021 [==============================] - 0s 150us/sample - loss: 1.4710 - mse: 1.4710 - val_loss: 0.8490 - val_mse: 0.8490
Epoch 8/50
500/3021 [===>..........................] - ETA: 0s - loss: 1.4242 - mse: 1.4242
3021/3021 [==============================] - 0s 144us/sample - loss: 1.2714 - mse: 1.2714 - val_loss: 0.4991 - val_mse: 0.4991
Epoch 9/50
500/3021 [===>..........................] - ETA: 0s - loss: 1.0797 - mse: 1.0797
3021/3021 [==============================] - 0s 136us/sample - loss: 1.0838 - mse: 1.0838 - val_loss: 0.4748 - val_mse: 0.4748
Epoch 10/50
500/3021 [===>..........................] - ETA: 0s - loss: 1.1257 - mse: 1.1257
3021/3021 [==============================] - 0s 144us/sample - loss: 1.0708 - mse: 1.0708 - val_loss: 0.3610 - val_mse: 0.3610
Epoch 11/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.9541 - mse: 0.9541
3021/3021 [==============================] - 0s 149us/sample - loss: 0.9549 - mse: 0.9549 - val_loss: 0.4501 - val_mse: 0.4501
Epoch 12/50
500/3021 [===>..........................] - ETA: 0s - loss: 1.0381 - mse: 1.0381
3021/3021 [==============================] - 0s 143us/sample - loss: 1.0203 - mse: 1.0203 - val_loss: 0.5520 - val_mse: 0.5520
Epoch 13/50
500/3021 [===>..........................] - ETA: 0s - loss: 1.1510 - mse: 1.1510
3021/3021 [==============================] - 0s 139us/sample - loss: 1.0842 - mse: 1.0842 - val_loss: 0.4351 - val_mse: 0.4351
Epoch 14/50
500/3021 [===>..........................] - ETA: 0s - loss: 1.0800 - mse: 1.0800
3021/3021 [==============================] - 0s 139us/sample - loss: 1.0033 - mse: 1.0033 - val_loss: 0.2629 - val_mse: 0.2629
Epoch 15/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.8744 - mse: 0.8744
3021/3021 [==============================] - 0s 150us/sample - loss: 0.8587 - mse: 0.8587 - val_loss: 0.4079 - val_mse: 0.4079
Epoch 16/50
500/3021 [===>..........................] - ETA: 0s - loss: 1.0979 - mse: 1.0979
3021/3021 [==============================] - 0s 155us/sample - loss: 1.0299 - mse: 1.0299 - val_loss: 0.6724 - val_mse: 0.6724
Epoch 17/50
500/3021 [===>..........................] - ETA: 0s - loss: 1.3766 - mse: 1.3766
3021/3021 [==============================] - 1s 173us/sample - loss: 1.0267 - mse: 1.0267 - val_loss: 0.1789 - val_mse: 0.1789
Epoch 18/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.7670 - mse: 0.7670
3021/3021 [==============================] - 0s 154us/sample - loss: 0.8893 - mse: 0.8893 - val_loss: 0.4038 - val_mse: 0.4038
Epoch 19/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.8542 - mse: 0.8542
3021/3021 [==============================] - 0s 144us/sample - loss: 0.8893 - mse: 0.8893 - val_loss: 0.2425 - val_mse: 0.2425
Epoch 20/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.7598 - mse: 0.7598
3021/3021 [==============================] - 0s 163us/sample - loss: 0.8503 - mse: 0.8503 - val_loss: 0.2423 - val_mse: 0.2423
Epoch 21/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.7845 - mse: 0.7845
3021/3021 [==============================] - 0s 146us/sample - loss: 0.7613 - mse: 0.7613 - val_loss: 0.2416 - val_mse: 0.2416
Epoch 22/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.6809 - mse: 0.6809
3021/3021 [==============================] - 0s 145us/sample - loss: 0.7223 - mse: 0.7223 - val_loss: 0.2528 - val_mse: 0.2528
Epoch 23/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.6921 - mse: 0.6921
3021/3021 [==============================] - 0s 138us/sample - loss: 0.7343 - mse: 0.7343 - val_loss: 0.2251 - val_mse: 0.2251
Epoch 24/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.6549 - mse: 0.6549
3021/3021 [==============================] - 0s 136us/sample - loss: 0.6723 - mse: 0.6723 - val_loss: 0.2180 - val_mse: 0.2180
Epoch 25/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.8276 - mse: 0.8276
3021/3021 [==============================] - 0s 143us/sample - loss: 0.7067 - mse: 0.7067 - val_loss: 0.3074 - val_mse: 0.3074
Epoch 26/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.7805 - mse: 0.7805
3021/3021 [==============================] - 0s 141us/sample - loss: 0.6661 - mse: 0.6661 - val_loss: 0.1655 - val_mse: 0.1655
Epoch 27/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.6373 - mse: 0.6373
3021/3021 [==============================] - 0s 135us/sample - loss: 0.7251 - mse: 0.7251 - val_loss: 0.2221 - val_mse: 0.2221
Epoch 28/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.7653 - mse: 0.7653
3021/3021 [==============================] - 0s 133us/sample - loss: 0.7433 - mse: 0.7433 - val_loss: 0.5183 - val_mse: 0.5183
Epoch 29/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.9096 - mse: 0.9096
3021/3021 [==============================] - 0s 139us/sample - loss: 0.7411 - mse: 0.7411 - val_loss: 0.1641 - val_mse: 0.1641
Epoch 30/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.5629 - mse: 0.5629
3021/3021 [==============================] - 0s 135us/sample - loss: 0.5548 - mse: 0.5548 - val_loss: 0.1389 - val_mse: 0.1389
Epoch 31/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.4960 - mse: 0.4960
3021/3021 [==============================] - 0s 135us/sample - loss: 0.5951 - mse: 0.5951 - val_loss: 0.1366 - val_mse: 0.1366
Epoch 32/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.5143 - mse: 0.5143
3021/3021 [==============================] - 0s 139us/sample - loss: 0.5749 - mse: 0.5749 - val_loss: 0.1376 - val_mse: 0.1376
Epoch 33/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.5598 - mse: 0.5598
3021/3021 [==============================] - 0s 142us/sample - loss: 0.5457 - mse: 0.5457 - val_loss: 0.2486 - val_mse: 0.2486
Epoch 34/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.6068 - mse: 0.6068
3021/3021 [==============================] - 0s 140us/sample - loss: 0.5426 - mse: 0.5426 - val_loss: 0.1745 - val_mse: 0.1745
Epoch 35/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.6505 - mse: 0.6505
3021/3021 [==============================] - 0s 136us/sample - loss: 0.5496 - mse: 0.5496 - val_loss: 0.2383 - val_mse: 0.2383
Epoch 36/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.5435 - mse: 0.5435
3021/3021 [==============================] - 0s 129us/sample - loss: 0.5437 - mse: 0.5437 - val_loss: 0.1264 - val_mse: 0.1264
Epoch 37/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.4786 - mse: 0.4786
3021/3021 [==============================] - 0s 151us/sample - loss: 0.4578 - mse: 0.4578 - val_loss: 0.0951 - val_mse: 0.0951
Epoch 38/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.4307 - mse: 0.4307
3021/3021 [==============================] - 0s 138us/sample - loss: 0.4590 - mse: 0.4590 - val_loss: 0.1803 - val_mse: 0.1803
Epoch 39/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.4538 - mse: 0.4538
3021/3021 [==============================] - 0s 141us/sample - loss: 0.4505 - mse: 0.4505 - val_loss: 0.1977 - val_mse: 0.1977
Epoch 40/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.6623 - mse: 0.6623
3021/3021 [==============================] - 0s 135us/sample - loss: 0.5553 - mse: 0.5553 - val_loss: 0.2836 - val_mse: 0.2836
Epoch 41/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.5316 - mse: 0.5316
3021/3021 [==============================] - 0s 143us/sample - loss: 0.4977 - mse: 0.4977 - val_loss: 0.1468 - val_mse: 0.1468
Epoch 42/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.4750 - mse: 0.4750
3021/3021 [==============================] - 0s 143us/sample - loss: 0.4668 - mse: 0.4668 - val_loss: 0.1760 - val_mse: 0.1760
Epoch 43/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.3423 - mse: 0.3423
3021/3021 [==============================] - 0s 140us/sample - loss: 0.4004 - mse: 0.4004 - val_loss: 0.1416 - val_mse: 0.1416
Epoch 44/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.4625 - mse: 0.4625
3021/3021 [==============================] - 0s 132us/sample - loss: 0.4005 - mse: 0.4005 - val_loss: 0.2403 - val_mse: 0.2403
Epoch 45/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.4194 - mse: 0.4194
3021/3021 [==============================] - 0s 143us/sample - loss: 0.4429 - mse: 0.4429 - val_loss: 0.2089 - val_mse: 0.2089
Epoch 46/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.5367 - mse: 0.5367
3021/3021 [==============================] - 0s 147us/sample - loss: 0.4798 - mse: 0.4798 - val_loss: 0.1659 - val_mse: 0.1659
Epoch 47/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.4180 - mse: 0.4180
3021/3021 [==============================] - 0s 147us/sample - loss: 0.4079 - mse: 0.4079 - val_loss: 0.1233 - val_mse: 0.1233
Epoch 48/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.3852 - mse: 0.3852
3021/3021 [==============================] - 0s 139us/sample - loss: 0.3984 - mse: 0.3984 - val_loss: 0.3404 - val_mse: 0.3404
Epoch 49/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.5010 - mse: 0.5010
3021/3021 [==============================] - 0s 140us/sample - loss: 0.4097 - mse: 0.4097 - val_loss: 0.2645 - val_mse: 0.2645
Epoch 50/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.5870 - mse: 0.5870
3021/3021 [==============================] - 0s 138us/sample - loss: 0.4123 - mse: 0.4123 - val_loss: 0.1565 - val_mse: 0.1565Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-05-04T01-06-17Z
Training run 29/46 (flags = list(392, 128, 1e-04, 200, 50, "sigmoid", "sigmoid", 0.5, 0.1))
Using run directory runs/2020-05-04T01-06-43Z
> FLAGS <- flags(
+ flag_numeric("nodes1", 128),
+ flag_numeric("nodes2", 128),
+ flag_numeric("batch_size", 100),
+ flag_string("activation1" .... [TRUNCATED]
> model = keras_model_sequential()
> model %>%
+ layer_dense(units=FLAGS$nodes1, activation=FLAGS$activation1, input_shape=dim(efw_train2)[2]) %>%
+ layer_dropout(FLAGS$dropout1) %> .... [TRUNCATED]
> model %>% compile(
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ loss = 'mse',
+ metrics = c('mse')
+ )
> model %>% fit(
+ as.matrix(efw_train2), train2Label,
+ epochs=FLAGS$epochs,
+ batch_size=FLAGS$batch_size,
+ validation_data=list(as.matrix( .... [TRUNCATED]
Train on 3021 samples, validate on 334 samples
Epoch 1/50
200/3021 [>.............................] - ETA: 3s - loss: 30.9685 - mse: 30.9685
2600/3021 [========================>.....] - ETA: 0s - loss: 28.9217 - mse: 28.9217
3021/3021 [==============================] - 1s 260us/sample - loss: 28.6186 - mse: 28.6186 - val_loss: 26.2953 - val_mse: 26.2952
Epoch 2/50
200/3021 [>.............................] - ETA: 0s - loss: 26.8646 - mse: 26.8646
2600/3021 [========================>.....] - ETA: 0s - loss: 25.7164 - mse: 25.7164
3021/3021 [==============================] - 0s 157us/sample - loss: 25.2444 - mse: 25.2444 - val_loss: 22.9429 - val_mse: 22.9429
Epoch 3/50
200/3021 [>.............................] - ETA: 0s - loss: 22.0335 - mse: 22.0335
2600/3021 [========================>.....] - ETA: 0s - loss: 21.8560 - mse: 21.8560
3021/3021 [==============================] - 1s 176us/sample - loss: 21.6836 - mse: 21.6836 - val_loss: 19.9517 - val_mse: 19.9517
Epoch 4/50
200/3021 [>.............................] - ETA: 0s - loss: 19.9836 - mse: 19.9836
2800/3021 [==========================>...] - ETA: 0s - loss: 19.0994 - mse: 19.0994
3021/3021 [==============================] - 0s 154us/sample - loss: 18.9720 - mse: 18.9720 - val_loss: 17.2673 - val_mse: 17.2673
Epoch 5/50
200/3021 [>.............................] - ETA: 0s - loss: 17.1154 - mse: 17.1154
2600/3021 [========================>.....] - ETA: 0s - loss: 16.5394 - mse: 16.5394
3021/3021 [==============================] - 0s 158us/sample - loss: 16.4357 - mse: 16.4357 - val_loss: 14.8847 - val_mse: 14.8847
Epoch 6/50
200/3021 [>.............................] - ETA: 0s - loss: 14.6756 - mse: 14.6756
2200/3021 [====================>.........] - ETA: 0s - loss: 14.3600 - mse: 14.3601
3021/3021 [==============================] - 0s 152us/sample - loss: 13.9824 - mse: 13.9824 - val_loss: 12.7548 - val_mse: 12.7548
Epoch 7/50
200/3021 [>.............................] - ETA: 0s - loss: 12.3098 - mse: 12.3098
2600/3021 [========================>.....] - ETA: 0s - loss: 12.2035 - mse: 12.2035
3021/3021 [==============================] - 0s 163us/sample - loss: 12.1172 - mse: 12.1172 - val_loss: 10.8814 - val_mse: 10.8814
Epoch 8/50
200/3021 [>.............................] - ETA: 0s - loss: 11.3027 - mse: 11.3027
2600/3021 [========================>.....] - ETA: 0s - loss: 10.5823 - mse: 10.5823
3021/3021 [==============================] - 0s 162us/sample - loss: 10.4578 - mse: 10.4578 - val_loss: 9.2313 - val_mse: 9.2313
Epoch 9/50
200/3021 [>.............................] - ETA: 0s - loss: 9.5602 - mse: 9.5602
2200/3021 [====================>.........] - ETA: 0s - loss: 9.0253 - mse: 9.0253
3021/3021 [==============================] - 1s 185us/sample - loss: 8.8749 - mse: 8.8749 - val_loss: 7.7888 - val_mse: 7.7888
Epoch 10/50
200/3021 [>.............................] - ETA: 0s - loss: 8.0443 - mse: 8.0443
2400/3021 [======================>.......] - ETA: 0s - loss: 7.6385 - mse: 7.6385
3021/3021 [==============================] - 1s 170us/sample - loss: 7.5471 - mse: 7.5471 - val_loss: 6.5300 - val_mse: 6.5300
Epoch 11/50
200/3021 [>.............................] - ETA: 0s - loss: 7.1639 - mse: 7.1639
2200/3021 [====================>.........] - ETA: 0s - loss: 6.5648 - mse: 6.5648
3021/3021 [==============================] - 1s 186us/sample - loss: 6.3974 - mse: 6.3974 - val_loss: 5.4515 - val_mse: 5.4515
Epoch 12/50
200/3021 [>.............................] - ETA: 0s - loss: 5.5641 - mse: 5.5641
2600/3021 [========================>.....] - ETA: 0s - loss: 5.4416 - mse: 5.4416
3021/3021 [==============================] - 1s 173us/sample - loss: 5.4078 - mse: 5.4078 - val_loss: 4.5280 - val_mse: 4.5280
Epoch 13/50
200/3021 [>.............................] - ETA: 0s - loss: 4.8508 - mse: 4.8508
2600/3021 [========================>.....] - ETA: 0s - loss: 4.6787 - mse: 4.6787
3021/3021 [==============================] - 1s 176us/sample - loss: 4.6135 - mse: 4.6135 - val_loss: 3.7404 - val_mse: 3.7404
Epoch 14/50
200/3021 [>.............................] - ETA: 0s - loss: 4.4213 - mse: 4.4213
2400/3021 [======================>.......] - ETA: 0s - loss: 3.9342 - mse: 3.9342
3021/3021 [==============================] - 1s 177us/sample - loss: 3.8481 - mse: 3.8481 - val_loss: 3.0692 - val_mse: 3.0692
Epoch 15/50
200/3021 [>.............................] - ETA: 0s - loss: 3.2566 - mse: 3.2566
2400/3021 [======================>.......] - ETA: 0s - loss: 3.2770 - mse: 3.2770
3021/3021 [==============================] - 1s 177us/sample - loss: 3.2495 - mse: 3.2495 - val_loss: 2.5055 - val_mse: 2.5055
Epoch 16/50
200/3021 [>.............................] - ETA: 0s - loss: 2.9238 - mse: 2.9238
1800/3021 [================>.............] - ETA: 0s - loss: 2.7554 - mse: 2.7554
3021/3021 [==============================] - 0s 159us/sample - loss: 2.7226 - mse: 2.7226 - val_loss: 2.0404 - val_mse: 2.0404
Epoch 17/50
200/3021 [>.............................] - ETA: 0s - loss: 2.6019 - mse: 2.6019
2600/3021 [========================>.....] - ETA: 0s - loss: 2.3483 - mse: 2.3483
3021/3021 [==============================] - 0s 154us/sample - loss: 2.3321 - mse: 2.3321 - val_loss: 1.6562 - val_mse: 1.6562
Epoch 18/50
200/3021 [>.............................] - ETA: 0s - loss: 2.2110 - mse: 2.2110
2800/3021 [==========================>...] - ETA: 0s - loss: 1.9482 - mse: 1.9482
3021/3021 [==============================] - 0s 151us/sample - loss: 1.9347 - mse: 1.9347 - val_loss: 1.3434 - val_mse: 1.3434
Epoch 19/50
200/3021 [>.............................] - ETA: 0s - loss: 1.8269 - mse: 1.8269
2400/3021 [======================>.......] - ETA: 0s - loss: 1.7245 - mse: 1.7245
3021/3021 [==============================] - 0s 163us/sample - loss: 1.7278 - mse: 1.7278 - val_loss: 1.0830 - val_mse: 1.0830
Epoch 20/50
200/3021 [>.............................] - ETA: 0s - loss: 1.7407 - mse: 1.7407
1800/3021 [================>.............] - ETA: 0s - loss: 1.5849 - mse: 1.5849
3021/3021 [==============================] - 0s 159us/sample - loss: 1.5411 - mse: 1.5411 - val_loss: 0.8649 - val_mse: 0.8649
Epoch 21/50
200/3021 [>.............................] - ETA: 0s - loss: 1.2576 - mse: 1.2576
2600/3021 [========================>.....] - ETA: 0s - loss: 1.3757 - mse: 1.3757
3021/3021 [==============================] - 0s 165us/sample - loss: 1.3590 - mse: 1.3590 - val_loss: 0.6889 - val_mse: 0.6889
Epoch 22/50
200/3021 [>.............................] - ETA: 0s - loss: 1.2417 - mse: 1.2417
2000/3021 [==================>...........] - ETA: 0s - loss: 1.1673 - mse: 1.1673
3021/3021 [==============================] - 0s 159us/sample - loss: 1.1347 - mse: 1.1347 - val_loss: 0.5534 - val_mse: 0.5534
Epoch 23/50
200/3021 [>.............................] - ETA: 0s - loss: 1.2179 - mse: 1.2179
2600/3021 [========================>.....] - ETA: 0s - loss: 1.0256 - mse: 1.0256
3021/3021 [==============================] - 0s 153us/sample - loss: 1.0236 - mse: 1.0236 - val_loss: 0.4485 - val_mse: 0.4485
Epoch 24/50
200/3021 [>.............................] - ETA: 0s - loss: 1.0801 - mse: 1.0801
2200/3021 [====================>.........] - ETA: 0s - loss: 0.9603 - mse: 0.9603
3021/3021 [==============================] - 0s 154us/sample - loss: 0.9592 - mse: 0.9592 - val_loss: 0.3635 - val_mse: 0.3635
Epoch 25/50
200/3021 [>.............................] - ETA: 0s - loss: 1.0683 - mse: 1.0683
2600/3021 [========================>.....] - ETA: 0s - loss: 0.9512 - mse: 0.9512
3021/3021 [==============================] - 0s 153us/sample - loss: 0.9220 - mse: 0.9220 - val_loss: 0.2938 - val_mse: 0.2938
Epoch 26/50
200/3021 [>.............................] - ETA: 0s - loss: 0.7466 - mse: 0.7466
1800/3021 [================>.............] - ETA: 0s - loss: 0.7962 - mse: 0.7962
3021/3021 [==============================] - 0s 152us/sample - loss: 0.8188 - mse: 0.8188 - val_loss: 0.2424 - val_mse: 0.2424
Epoch 27/50
200/3021 [>.............................] - ETA: 0s - loss: 0.8922 - mse: 0.8922
2000/3021 [==================>...........] - ETA: 0s - loss: 0.7622 - mse: 0.7622
3021/3021 [==============================] - 0s 165us/sample - loss: 0.7701 - mse: 0.7701 - val_loss: 0.2033 - val_mse: 0.2033
Epoch 28/50
200/3021 [>.............................] - ETA: 0s - loss: 0.7849 - mse: 0.7849
2000/3021 [==================>...........] - ETA: 0s - loss: 0.7690 - mse: 0.7690
3021/3021 [==============================] - 0s 155us/sample - loss: 0.7536 - mse: 0.7536 - val_loss: 0.1730 - val_mse: 0.1730
Epoch 29/50
200/3021 [>.............................] - ETA: 0s - loss: 0.6613 - mse: 0.6613
2800/3021 [==========================>...] - ETA: 0s - loss: 0.7270 - mse: 0.7270
3021/3021 [==============================] - 0s 160us/sample - loss: 0.7336 - mse: 0.7336 - val_loss: 0.1491 - val_mse: 0.1491
Epoch 30/50
200/3021 [>.............................] - ETA: 0s - loss: 0.7460 - mse: 0.7460
2600/3021 [========================>.....] - ETA: 0s - loss: 0.7324 - mse: 0.7324
3021/3021 [==============================] - 0s 143us/sample - loss: 0.7191 - mse: 0.7191 - val_loss: 0.1305 - val_mse: 0.1305
Epoch 31/50
200/3021 [>.............................] - ETA: 0s - loss: 0.7041 - mse: 0.7041
2800/3021 [==========================>...] - ETA: 0s - loss: 0.6738 - mse: 0.6738
3021/3021 [==============================] - 0s 155us/sample - loss: 0.6847 - mse: 0.6847 - val_loss: 0.1168 - val_mse: 0.1168
Epoch 32/50
200/3021 [>.............................] - ETA: 0s - loss: 0.7982 - mse: 0.7982
2400/3021 [======================>.......] - ETA: 0s - loss: 0.6720 - mse: 0.6720
3021/3021 [==============================] - 0s 157us/sample - loss: 0.6752 - mse: 0.6752 - val_loss: 0.1065 - val_mse: 0.1065
Epoch 33/50
200/3021 [>.............................] - ETA: 0s - loss: 0.5212 - mse: 0.5212
2000/3021 [==================>...........] - ETA: 0s - loss: 0.6708 - mse: 0.6708
3021/3021 [==============================] - 0s 155us/sample - loss: 0.6716 - mse: 0.6716 - val_loss: 0.0987 - val_mse: 0.0987
Epoch 34/50
200/3021 [>.............................] - ETA: 0s - loss: 0.5833 - mse: 0.5833
3000/3021 [============================>.] - ETA: 0s - loss: 0.6606 - mse: 0.6606
3021/3021 [==============================] - 0s 148us/sample - loss: 0.6620 - mse: 0.6620 - val_loss: 0.0918 - val_mse: 0.0918
Epoch 35/50
200/3021 [>.............................] - ETA: 0s - loss: 0.5479 - mse: 0.5479
2000/3021 [==================>...........] - ETA: 0s - loss: 0.6591 - mse: 0.6591
3021/3021 [==============================] - 0s 149us/sample - loss: 0.6587 - mse: 0.6587 - val_loss: 0.0868 - val_mse: 0.0868
Epoch 36/50
200/3021 [>.............................] - ETA: 0s - loss: 0.7271 - mse: 0.7271
2600/3021 [========================>.....] - ETA: 0s - loss: 0.6488 - mse: 0.6488
3021/3021 [==============================] - 0s 163us/sample - loss: 0.6638 - mse: 0.6638 - val_loss: 0.0834 - val_mse: 0.0834
Epoch 37/50
200/3021 [>.............................] - ETA: 0s - loss: 0.6048 - mse: 0.6048
2800/3021 [==========================>...] - ETA: 0s - loss: 0.6538 - mse: 0.6538
3021/3021 [==============================] - 0s 150us/sample - loss: 0.6575 - mse: 0.6575 - val_loss: 0.0809 - val_mse: 0.0809
Epoch 38/50
200/3021 [>.............................] - ETA: 0s - loss: 0.6335 - mse: 0.6335
2400/3021 [======================>.......] - ETA: 0s - loss: 0.6406 - mse: 0.6406
3021/3021 [==============================] - 0s 160us/sample - loss: 0.6506 - mse: 0.6506 - val_loss: 0.0790 - val_mse: 0.0790
Epoch 39/50
200/3021 [>.............................] - ETA: 0s - loss: 0.7117 - mse: 0.7117
2000/3021 [==================>...........] - ETA: 0s - loss: 0.6803 - mse: 0.6803
3021/3021 [==============================] - 1s 183us/sample - loss: 0.6769 - mse: 0.6769 - val_loss: 0.0770 - val_mse: 0.0770
Epoch 40/50
200/3021 [>.............................] - ETA: 0s - loss: 0.5506 - mse: 0.5506
2400/3021 [======================>.......] - ETA: 0s - loss: 0.6326 - mse: 0.6326
3021/3021 [==============================] - 1s 172us/sample - loss: 0.6437 - mse: 0.6437 - val_loss: 0.0758 - val_mse: 0.0758
Epoch 41/50
200/3021 [>.............................] - ETA: 0s - loss: 0.6524 - mse: 0.6524
2400/3021 [======================>.......] - ETA: 0s - loss: 0.6965 - mse: 0.6965
3021/3021 [==============================] - 0s 164us/sample - loss: 0.7040 - mse: 0.7040 - val_loss: 0.0749 - val_mse: 0.0749
Epoch 42/50
200/3021 [>.............................] - ETA: 0s - loss: 0.5114 - mse: 0.5114
2400/3021 [======================>.......] - ETA: 0s - loss: 0.6317 - mse: 0.6317
3021/3021 [==============================] - 1s 171us/sample - loss: 0.6381 - mse: 0.6381 - val_loss: 0.0741 - val_mse: 0.0741
Epoch 43/50
200/3021 [>.............................] - ETA: 0s - loss: 0.5837 - mse: 0.5837
2200/3021 [====================>.........] - ETA: 0s - loss: 0.6671 - mse: 0.6671
3021/3021 [==============================] - 1s 169us/sample - loss: 0.6736 - mse: 0.6736 - val_loss: 0.0732 - val_mse: 0.0732
Epoch 44/50
200/3021 [>.............................] - ETA: 0s - loss: 0.6267 - mse: 0.6267
2400/3021 [======================>.......] - ETA: 0s - loss: 0.6776 - mse: 0.6776
3021/3021 [==============================] - 1s 173us/sample - loss: 0.6787 - mse: 0.6787 - val_loss: 0.0722 - val_mse: 0.0722
Epoch 45/50
200/3021 [>.............................] - ETA: 0s - loss: 0.6587 - mse: 0.6587
2400/3021 [======================>.......] - ETA: 0s - loss: 0.6559 - mse: 0.6559
3021/3021 [==============================] - 1s 166us/sample - loss: 0.6713 - mse: 0.6713 - val_loss: 0.0714 - val_mse: 0.0714
Epoch 46/50
200/3021 [>.............................] - ETA: 0s - loss: 0.5157 - mse: 0.5157
2600/3021 [========================>.....] - ETA: 0s - loss: 0.6360 - mse: 0.6360
3021/3021 [==============================] - 0s 156us/sample - loss: 0.6403 - mse: 0.6403 - val_loss: 0.0704 - val_mse: 0.0704
Epoch 47/50
200/3021 [>.............................] - ETA: 0s - loss: 0.5330 - mse: 0.5330
2600/3021 [========================>.....] - ETA: 0s - loss: 0.6507 - mse: 0.6507
3021/3021 [==============================] - 0s 152us/sample - loss: 0.6511 - mse: 0.6511 - val_loss: 0.0699 - val_mse: 0.0699
Epoch 48/50
200/3021 [>.............................] - ETA: 0s - loss: 0.6592 - mse: 0.6592
2400/3021 [======================>.......] - ETA: 0s - loss: 0.6515 - mse: 0.6515
3021/3021 [==============================] - 0s 161us/sample - loss: 0.6504 - mse: 0.6504 - val_loss: 0.0693 - val_mse: 0.0693
Epoch 49/50
200/3021 [>.............................] - ETA: 0s - loss: 0.6356 - mse: 0.6356
2200/3021 [====================>.........] - ETA: 0s - loss: 0.6674 - mse: 0.6674
3021/3021 [==============================] - 0s 158us/sample - loss: 0.6666 - mse: 0.6666 - val_loss: 0.0684 - val_mse: 0.0684
Epoch 50/50
200/3021 [>.............................] - ETA: 0s - loss: 0.7570 - mse: 0.7570
2800/3021 [==========================>...] - ETA: 0s - loss: 0.6907 - mse: 0.6907
3021/3021 [==============================] - 0s 155us/sample - loss: 0.6895 - mse: 0.6895 - val_loss: 0.0680 - val_mse: 0.0680Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-05-04T01-06-43Z
Training run 30/46 (flags = list(392, 64, 0.05, 100, 50, "tanh", "tanh", 0.5, 0.1))
Using run directory runs/2020-05-04T01-07-12Z
> FLAGS <- flags(
+ flag_numeric("nodes1", 128),
+ flag_numeric("nodes2", 128),
+ flag_numeric("batch_size", 100),
+ flag_string("activation1" .... [TRUNCATED]
> model = keras_model_sequential()
> model %>%
+ layer_dense(units=FLAGS$nodes1, activation=FLAGS$activation1, input_shape=dim(efw_train2)[2]) %>%
+ layer_dropout(FLAGS$dropout1) %> .... [TRUNCATED]
> model %>% compile(
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ loss = 'mse',
+ metrics = c('mse')
+ )
> model %>% fit(
+ as.matrix(efw_train2), train2Label,
+ epochs=FLAGS$epochs,
+ batch_size=FLAGS$batch_size,
+ validation_data=list(as.matrix( .... [TRUNCATED]
Train on 3021 samples, validate on 334 samples
Epoch 1/50
100/3021 [..............................] - ETA: 6s - loss: 46.4587 - mse: 46.4587
1600/3021 [==============>...............] - ETA: 0s - loss: 27.9553 - mse: 27.9553
3000/3021 [============================>.] - ETA: 0s - loss: 16.5414 - mse: 16.5414
3021/3021 [==============================] - 1s 273us/sample - loss: 16.4384 - mse: 16.4384 - val_loss: 0.7022 - val_mse: 0.7022
Epoch 2/50
100/3021 [..............................] - ETA: 0s - loss: 1.7010 - mse: 1.7010
1700/3021 [===============>..............] - ETA: 0s - loss: 1.1785 - mse: 1.1785
3021/3021 [==============================] - 1s 175us/sample - loss: 0.9994 - mse: 0.9994 - val_loss: 0.2586 - val_mse: 0.2586
Epoch 3/50
100/3021 [..............................] - ETA: 0s - loss: 0.6032 - mse: 0.6032
1600/3021 [==============>...............] - ETA: 0s - loss: 0.6107 - mse: 0.6107
2900/3021 [===========================>..] - ETA: 0s - loss: 0.5730 - mse: 0.5730
3021/3021 [==============================] - 1s 177us/sample - loss: 0.5752 - mse: 0.5752 - val_loss: 0.1804 - val_mse: 0.1804
Epoch 4/50
100/3021 [..............................] - ETA: 0s - loss: 0.4825 - mse: 0.4825
1300/3021 [===========>..................] - ETA: 0s - loss: 0.4763 - mse: 0.4763
3000/3021 [============================>.] - ETA: 0s - loss: 0.4932 - mse: 0.4932
3021/3021 [==============================] - 1s 173us/sample - loss: 0.4927 - mse: 0.4927 - val_loss: 0.1997 - val_mse: 0.1997
Epoch 5/50
100/3021 [..............................] - ETA: 0s - loss: 0.4404 - mse: 0.4404
1700/3021 [===============>..............] - ETA: 0s - loss: 0.4940 - mse: 0.4940
3021/3021 [==============================] - 1s 173us/sample - loss: 0.4846 - mse: 0.4846 - val_loss: 0.1450 - val_mse: 0.1450
Epoch 6/50
100/3021 [..............................] - ETA: 0s - loss: 0.4907 - mse: 0.4907
1100/3021 [=========>....................] - ETA: 0s - loss: 0.4264 - mse: 0.4264
2800/3021 [==========================>...] - ETA: 0s - loss: 0.4271 - mse: 0.4271
3021/3021 [==============================] - 1s 168us/sample - loss: 0.4243 - mse: 0.4243 - val_loss: 0.1554 - val_mse: 0.1554
Epoch 7/50
100/3021 [..............................] - ETA: 0s - loss: 0.4009 - mse: 0.4009
1600/3021 [==============>...............] - ETA: 0s - loss: 0.4155 - mse: 0.4155
3021/3021 [==============================] - 1s 172us/sample - loss: 0.4360 - mse: 0.4360 - val_loss: 0.3449 - val_mse: 0.3449
Epoch 8/50
100/3021 [..............................] - ETA: 0s - loss: 0.6165 - mse: 0.6165
1500/3021 [=============>................] - ETA: 0s - loss: 0.5063 - mse: 0.5063
3021/3021 [==============================] - 1s 170us/sample - loss: 0.4904 - mse: 0.4904 - val_loss: 0.2542 - val_mse: 0.2542
Epoch 9/50
100/3021 [..............................] - ETA: 0s - loss: 0.6343 - mse: 0.6343
1500/3021 [=============>................] - ETA: 0s - loss: 0.5122 - mse: 0.5122
3000/3021 [============================>.] - ETA: 0s - loss: 0.5128 - mse: 0.5128
3021/3021 [==============================] - 1s 186us/sample - loss: 0.5103 - mse: 0.5103 - val_loss: 0.1368 - val_mse: 0.1368
Epoch 10/50
100/3021 [..............................] - ETA: 0s - loss: 0.4569 - mse: 0.4569
1300/3021 [===========>..................] - ETA: 0s - loss: 0.3997 - mse: 0.3997
2800/3021 [==========================>...] - ETA: 0s - loss: 0.4845 - mse: 0.4845
3021/3021 [==============================] - 1s 208us/sample - loss: 0.4868 - mse: 0.4868 - val_loss: 0.4230 - val_mse: 0.4230
Epoch 11/50
100/3021 [..............................] - ETA: 0s - loss: 0.8261 - mse: 0.8261
1500/3021 [=============>................] - ETA: 0s - loss: 0.5628 - mse: 0.5628
2900/3021 [===========================>..] - ETA: 0s - loss: 0.4818 - mse: 0.4818
3021/3021 [==============================] - 1s 180us/sample - loss: 0.4755 - mse: 0.4755 - val_loss: 0.0992 - val_mse: 0.0992
Epoch 12/50
100/3021 [..............................] - ETA: 0s - loss: 0.3106 - mse: 0.3106
1300/3021 [===========>..................] - ETA: 0s - loss: 0.3466 - mse: 0.3466
3000/3021 [============================>.] - ETA: 0s - loss: 0.3452 - mse: 0.3452
3021/3021 [==============================] - 1s 176us/sample - loss: 0.3452 - mse: 0.3452 - val_loss: 0.1551 - val_mse: 0.1551
Epoch 13/50
100/3021 [..............................] - ETA: 0s - loss: 0.3462 - mse: 0.3462
1700/3021 [===============>..............] - ETA: 0s - loss: 0.3539 - mse: 0.3539
3021/3021 [==============================] - 1s 168us/sample - loss: 0.4209 - mse: 0.4209 - val_loss: 0.3465 - val_mse: 0.3465
Epoch 14/50
100/3021 [..............................] - ETA: 0s - loss: 0.6170 - mse: 0.6170
1700/3021 [===============>..............] - ETA: 0s - loss: 0.5316 - mse: 0.5316
3021/3021 [==============================] - 1s 172us/sample - loss: 0.4947 - mse: 0.4947 - val_loss: 0.1856 - val_mse: 0.1856
Epoch 15/50
100/3021 [..............................] - ETA: 0s - loss: 0.4967 - mse: 0.4967
1500/3021 [=============>................] - ETA: 0s - loss: 0.4221 - mse: 0.4221
3000/3021 [============================>.] - ETA: 0s - loss: 0.4299 - mse: 0.4299
3021/3021 [==============================] - 1s 168us/sample - loss: 0.4296 - mse: 0.4296 - val_loss: 0.7993 - val_mse: 0.7993
Epoch 16/50
100/3021 [..............................] - ETA: 0s - loss: 1.0491 - mse: 1.0491
1600/3021 [==============>...............] - ETA: 0s - loss: 0.5721 - mse: 0.5721
3021/3021 [==============================] - 1s 167us/sample - loss: 0.4992 - mse: 0.4992 - val_loss: 0.1550 - val_mse: 0.1550
Epoch 17/50
100/3021 [..............................] - ETA: 0s - loss: 0.4275 - mse: 0.4275
1500/3021 [=============>................] - ETA: 0s - loss: 0.5110 - mse: 0.5110
3000/3021 [============================>.] - ETA: 0s - loss: 0.6097 - mse: 0.6097
3021/3021 [==============================] - 1s 169us/sample - loss: 0.6099 - mse: 0.6099 - val_loss: 0.3328 - val_mse: 0.3328
Epoch 18/50
100/3021 [..............................] - ETA: 0s - loss: 0.4948 - mse: 0.4948
1600/3021 [==============>...............] - ETA: 0s - loss: 0.5244 - mse: 0.5244
3021/3021 [==============================] - 1s 172us/sample - loss: 0.5363 - mse: 0.5363 - val_loss: 0.2493 - val_mse: 0.2493
Epoch 19/50
100/3021 [..............................] - ETA: 0s - loss: 0.5269 - mse: 0.5269
1000/3021 [========>.....................] - ETA: 0s - loss: 0.6491 - mse: 0.6491
2600/3021 [========================>.....] - ETA: 0s - loss: 0.5937 - mse: 0.5937
3021/3021 [==============================] - 1s 175us/sample - loss: 0.5807 - mse: 0.5807 - val_loss: 0.2902 - val_mse: 0.2902
Epoch 20/50
100/3021 [..............................] - ETA: 0s - loss: 0.5536 - mse: 0.5536
1400/3021 [============>.................] - ETA: 0s - loss: 0.6647 - mse: 0.6647
2800/3021 [==========================>...] - ETA: 0s - loss: 0.5787 - mse: 0.5787
3021/3021 [==============================] - 1s 175us/sample - loss: 0.5717 - mse: 0.5717 - val_loss: 0.1511 - val_mse: 0.1511
Epoch 21/50
100/3021 [..............................] - ETA: 0s - loss: 0.4467 - mse: 0.4467
1700/3021 [===============>..............] - ETA: 0s - loss: 0.5010 - mse: 0.5010
3021/3021 [==============================] - 1s 169us/sample - loss: 0.5330 - mse: 0.5330 - val_loss: 0.3617 - val_mse: 0.3617
Epoch 22/50
100/3021 [..............................] - ETA: 0s - loss: 0.5460 - mse: 0.5460
1700/3021 [===============>..............] - ETA: 0s - loss: 0.7047 - mse: 0.7047
3021/3021 [==============================] - 1s 169us/sample - loss: 0.6751 - mse: 0.6751 - val_loss: 0.1681 - val_mse: 0.1681
Epoch 23/50
100/3021 [..............................] - ETA: 0s - loss: 0.4413 - mse: 0.4413
1600/3021 [==============>...............] - ETA: 0s - loss: 0.4907 - mse: 0.4907
3021/3021 [==============================] - 0s 165us/sample - loss: 0.4710 - mse: 0.4710 - val_loss: 0.7183 - val_mse: 0.7183
Epoch 24/50
100/3021 [..............................] - ETA: 0s - loss: 0.9564 - mse: 0.9564
1700/3021 [===============>..............] - ETA: 0s - loss: 0.5737 - mse: 0.5737
3021/3021 [==============================] - 1s 170us/sample - loss: 0.5356 - mse: 0.5356 - val_loss: 0.2338 - val_mse: 0.2338
Epoch 25/50
100/3021 [..............................] - ETA: 0s - loss: 0.4150 - mse: 0.4150
1100/3021 [=========>....................] - ETA: 0s - loss: 0.4714 - mse: 0.4714
2700/3021 [=========================>....] - ETA: 0s - loss: 0.4317 - mse: 0.4317
3021/3021 [==============================] - 1s 171us/sample - loss: 0.4174 - mse: 0.4174 - val_loss: 0.1905 - val_mse: 0.1905
Epoch 26/50
100/3021 [..............................] - ETA: 0s - loss: 0.3245 - mse: 0.3245
1700/3021 [===============>..............] - ETA: 0s - loss: 0.4565 - mse: 0.4565
3021/3021 [==============================] - 1s 170us/sample - loss: 0.4769 - mse: 0.4769 - val_loss: 0.1831 - val_mse: 0.1831
Epoch 27/50
100/3021 [..............................] - ETA: 0s - loss: 0.3891 - mse: 0.3891
1000/3021 [========>.....................] - ETA: 0s - loss: 0.4151 - mse: 0.4151
2800/3021 [==========================>...] - ETA: 0s - loss: 0.5078 - mse: 0.5078
3021/3021 [==============================] - 1s 170us/sample - loss: 0.5267 - mse: 0.5267 - val_loss: 0.6957 - val_mse: 0.6957
Epoch 28/50
100/3021 [..............................] - ETA: 0s - loss: 1.1381 - mse: 1.1381
1700/3021 [===============>..............] - ETA: 0s - loss: 0.6831 - mse: 0.6831
3021/3021 [==============================] - 1s 170us/sample - loss: 0.6326 - mse: 0.6326 - val_loss: 0.1568 - val_mse: 0.1568
Epoch 29/50
100/3021 [..............................] - ETA: 0s - loss: 0.3748 - mse: 0.3748
1700/3021 [===============>..............] - ETA: 0s - loss: 0.4580 - mse: 0.4580
3021/3021 [==============================] - 0s 163us/sample - loss: 0.5893 - mse: 0.5893 - val_loss: 1.1901 - val_mse: 1.1901
Epoch 30/50
100/3021 [..............................] - ETA: 0s - loss: 1.4633 - mse: 1.4633
1500/3021 [=============>................] - ETA: 0s - loss: 0.8868 - mse: 0.8868
2900/3021 [===========================>..] - ETA: 0s - loss: 0.7253 - mse: 0.7253
3021/3021 [==============================] - 1s 170us/sample - loss: 0.7129 - mse: 0.7129 - val_loss: 0.3406 - val_mse: 0.3406
Epoch 31/50
100/3021 [..............................] - ETA: 0s - loss: 0.4031 - mse: 0.4031
1600/3021 [==============>...............] - ETA: 0s - loss: 0.5521 - mse: 0.5521
3021/3021 [==============================] - 0s 165us/sample - loss: 0.5281 - mse: 0.5281 - val_loss: 0.2972 - val_mse: 0.2972
Epoch 32/50
100/3021 [..............................] - ETA: 0s - loss: 0.4361 - mse: 0.4361
1600/3021 [==============>...............] - ETA: 0s - loss: 0.4705 - mse: 0.4705
3000/3021 [============================>.] - ETA: 0s - loss: 0.4408 - mse: 0.4408
3021/3021 [==============================] - 1s 171us/sample - loss: 0.4404 - mse: 0.4404 - val_loss: 0.2274 - val_mse: 0.2274
Epoch 33/50
100/3021 [..............................] - ETA: 0s - loss: 0.4781 - mse: 0.4781
1700/3021 [===============>..............] - ETA: 0s - loss: 0.4312 - mse: 0.4312
3021/3021 [==============================] - 1s 170us/sample - loss: 0.4051 - mse: 0.4051 - val_loss: 0.3003 - val_mse: 0.3003
Epoch 34/50
100/3021 [..............................] - ETA: 0s - loss: 0.3536 - mse: 0.3536
1700/3021 [===============>..............] - ETA: 0s - loss: 0.4559 - mse: 0.4559
3021/3021 [==============================] - 1s 173us/sample - loss: 0.4490 - mse: 0.4490 - val_loss: 0.1462 - val_mse: 0.1462
Epoch 35/50
100/3021 [..............................] - ETA: 0s - loss: 0.3932 - mse: 0.3932
1100/3021 [=========>....................] - ETA: 0s - loss: 0.3589 - mse: 0.3589
2800/3021 [==========================>...] - ETA: 0s - loss: 0.3344 - mse: 0.3344
3021/3021 [==============================] - 1s 173us/sample - loss: 0.3354 - mse: 0.3354 - val_loss: 0.1858 - val_mse: 0.1858
Epoch 36/50
100/3021 [..............................] - ETA: 0s - loss: 0.3217 - mse: 0.3217
1700/3021 [===============>..............] - ETA: 0s - loss: 0.3793 - mse: 0.3793
3021/3021 [==============================] - 1s 166us/sample - loss: 0.3450 - mse: 0.3450 - val_loss: 0.1300 - val_mse: 0.1300
Epoch 37/50
100/3021 [..............................] - ETA: 0s - loss: 0.2456 - mse: 0.2456
1200/3021 [==========>...................] - ETA: 0s - loss: 0.2871 - mse: 0.2871
2900/3021 [===========================>..] - ETA: 0s - loss: 0.2813 - mse: 0.2813
3021/3021 [==============================] - 1s 180us/sample - loss: 0.2831 - mse: 0.2831 - val_loss: 0.2061 - val_mse: 0.2061
Epoch 38/50
100/3021 [..............................] - ETA: 0s - loss: 0.4021 - mse: 0.4021
1100/3021 [=========>....................] - ETA: 0s - loss: 0.3546 - mse: 0.3546
2800/3021 [==========================>...] - ETA: 0s - loss: 0.3927 - mse: 0.3927
3021/3021 [==============================] - 1s 171us/sample - loss: 0.3970 - mse: 0.3970 - val_loss: 0.2829 - val_mse: 0.2829
Epoch 39/50
100/3021 [..............................] - ETA: 0s - loss: 0.5679 - mse: 0.5679
1500/3021 [=============>................] - ETA: 0s - loss: 0.4396 - mse: 0.4396
3021/3021 [==============================] - 1s 191us/sample - loss: 0.3796 - mse: 0.3796 - val_loss: 0.1330 - val_mse: 0.1330
Epoch 40/50
100/3021 [..............................] - ETA: 0s - loss: 0.2467 - mse: 0.2467
1100/3021 [=========>....................] - ETA: 0s - loss: 0.3818 - mse: 0.3818
2800/3021 [==========================>...] - ETA: 0s - loss: 0.3518 - mse: 0.3518
3021/3021 [==============================] - 1s 176us/sample - loss: 0.3496 - mse: 0.3496 - val_loss: 0.1325 - val_mse: 0.1325
Epoch 41/50
100/3021 [..............................] - ETA: 0s - loss: 0.3126 - mse: 0.3126
1200/3021 [==========>...................] - ETA: 0s - loss: 0.3148 - mse: 0.3148
2800/3021 [==========================>...] - ETA: 0s - loss: 0.3193 - mse: 0.3193
3021/3021 [==============================] - 1s 173us/sample - loss: 0.3276 - mse: 0.3276 - val_loss: 0.1967 - val_mse: 0.1967
Epoch 42/50
100/3021 [..............................] - ETA: 0s - loss: 0.2922 - mse: 0.2922
1100/3021 [=========>....................] - ETA: 0s - loss: 0.3049 - mse: 0.3049
2800/3021 [==========================>...] - ETA: 0s - loss: 0.3008 - mse: 0.3008
3021/3021 [==============================] - 1s 172us/sample - loss: 0.3065 - mse: 0.3065 - val_loss: 0.2432 - val_mse: 0.2432
Epoch 43/50
100/3021 [..............................] - ETA: 0s - loss: 0.2684 - mse: 0.2684
1600/3021 [==============>...............] - ETA: 0s - loss: 0.4191 - mse: 0.4191
3021/3021 [==============================] - 0s 165us/sample - loss: 0.3694 - mse: 0.3694 - val_loss: 0.1444 - val_mse: 0.1444
Epoch 44/50
100/3021 [..............................] - ETA: 0s - loss: 0.3096 - mse: 0.3096
1500/3021 [=============>................] - ETA: 0s - loss: 0.3965 - mse: 0.3965
3000/3021 [============================>.] - ETA: 0s - loss: 0.3636 - mse: 0.3636
3021/3021 [==============================] - 1s 176us/sample - loss: 0.3623 - mse: 0.3623 - val_loss: 0.1117 - val_mse: 0.1117
Epoch 45/50
100/3021 [..............................] - ETA: 0s - loss: 0.2385 - mse: 0.2385
1500/3021 [=============>................] - ETA: 0s - loss: 0.2978 - mse: 0.2978
3021/3021 [==============================] - 1s 175us/sample - loss: 0.2989 - mse: 0.2989 - val_loss: 0.1404 - val_mse: 0.1404
Epoch 46/50
100/3021 [..............................] - ETA: 0s - loss: 0.2631 - mse: 0.2631
1600/3021 [==============>...............] - ETA: 0s - loss: 0.2979 - mse: 0.2979
3000/3021 [============================>.] - ETA: 0s - loss: 0.3101 - mse: 0.3101
3021/3021 [==============================] - 1s 173us/sample - loss: 0.3107 - mse: 0.3107 - val_loss: 0.2466 - val_mse: 0.2466
Epoch 47/50
100/3021 [..............................] - ETA: 0s - loss: 0.3129 - mse: 0.3129
1600/3021 [==============>...............] - ETA: 0s - loss: 0.3140 - mse: 0.3140
3000/3021 [============================>.] - ETA: 0s - loss: 0.2769 - mse: 0.2769
3021/3021 [==============================] - 1s 177us/sample - loss: 0.2763 - mse: 0.2763 - val_loss: 0.1257 - val_mse: 0.1257
Epoch 48/50
100/3021 [..............................] - ETA: 0s - loss: 0.2506 - mse: 0.2506
1500/3021 [=============>................] - ETA: 0s - loss: 0.2595 - mse: 0.2595
3000/3021 [============================>.] - ETA: 0s - loss: 0.2542 - mse: 0.2542
3021/3021 [==============================] - 1s 166us/sample - loss: 0.2542 - mse: 0.2542 - val_loss: 0.2062 - val_mse: 0.2062
Epoch 49/50
100/3021 [..............................] - ETA: 0s - loss: 0.3270 - mse: 0.3270
1700/3021 [===============>..............] - ETA: 0s - loss: 0.2778 - mse: 0.2778
3021/3021 [==============================] - 1s 182us/sample - loss: 0.2757 - mse: 0.2757 - val_loss: 0.1634 - val_mse: 0.1634
Epoch 50/50
100/3021 [..............................] - ETA: 0s - loss: 0.2986 - mse: 0.2986
1600/3021 [==============>...............] - ETA: 0s - loss: 0.2981 - mse: 0.2981
3021/3021 [==============================] - 0s 165us/sample - loss: 0.2702 - mse: 0.2702 - val_loss: 0.1444 - val_mse: 0.1444Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-05-04T01-07-12Z
Training run 31/46 (flags = list(128, 128, 0.01, 100, 30, "tanh", "relu", 0.5, 0.05))
Using run directory runs/2020-05-04T01-07-42Z
> FLAGS <- flags(
+ flag_numeric("nodes1", 128),
+ flag_numeric("nodes2", 128),
+ flag_numeric("batch_size", 100),
+ flag_string("activation1" .... [TRUNCATED]
> model = keras_model_sequential()
> model %>%
+ layer_dense(units=FLAGS$nodes1, activation=FLAGS$activation1, input_shape=dim(efw_train2)[2]) %>%
+ layer_dropout(FLAGS$dropout1) %> .... [TRUNCATED]
> model %>% compile(
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ loss = 'mse',
+ metrics = c('mse')
+ )
> model %>% fit(
+ as.matrix(efw_train2), train2Label,
+ epochs=FLAGS$epochs,
+ batch_size=FLAGS$batch_size,
+ validation_data=list(as.matrix( .... [TRUNCATED]
Train on 3021 samples, validate on 334 samples
Epoch 1/30
100/3021 [..............................] - ETA: 6s - loss: 41.3581 - mse: 41.3581
2400/3021 [======================>.......] - ETA: 0s - loss: 15.8969 - mse: 15.8969
3021/3021 [==============================] - 1s 256us/sample - loss: 13.2284 - mse: 13.2284 - val_loss: 0.8414 - val_mse: 0.8414
Epoch 2/30
100/3021 [..............................] - ETA: 0s - loss: 2.3426 - mse: 2.3426
1800/3021 [================>.............] - ETA: 0s - loss: 1.8783 - mse: 1.8783
3021/3021 [==============================] - 0s 159us/sample - loss: 1.6052 - mse: 1.6052 - val_loss: 0.3364 - val_mse: 0.3364
Epoch 3/30
100/3021 [..............................] - ETA: 0s - loss: 1.0044 - mse: 1.0044
2100/3021 [===================>..........] - ETA: 0s - loss: 0.8837 - mse: 0.8837
3021/3021 [==============================] - 0s 162us/sample - loss: 0.8445 - mse: 0.8445 - val_loss: 0.1853 - val_mse: 0.1853
Epoch 4/30
100/3021 [..............................] - ETA: 0s - loss: 0.8389 - mse: 0.8389
1400/3021 [============>.................] - ETA: 0s - loss: 0.7782 - mse: 0.7782
3021/3021 [==============================] - 0s 157us/sample - loss: 0.7252 - mse: 0.7252 - val_loss: 0.1582 - val_mse: 0.1582
Epoch 5/30
100/3021 [..............................] - ETA: 0s - loss: 0.6971 - mse: 0.6971
2400/3021 [======================>.......] - ETA: 0s - loss: 0.6152 - mse: 0.6152
3021/3021 [==============================] - 0s 153us/sample - loss: 0.6147 - mse: 0.6147 - val_loss: 0.1270 - val_mse: 0.1270
Epoch 6/30
100/3021 [..............................] - ETA: 0s - loss: 0.6019 - mse: 0.6019
2100/3021 [===================>..........] - ETA: 0s - loss: 0.6189 - mse: 0.6189
3021/3021 [==============================] - 0s 157us/sample - loss: 0.6136 - mse: 0.6136 - val_loss: 0.1824 - val_mse: 0.1824
Epoch 7/30
100/3021 [..............................] - ETA: 0s - loss: 0.6056 - mse: 0.6056
1900/3021 [=================>............] - ETA: 0s - loss: 0.5833 - mse: 0.5833
3021/3021 [==============================] - 0s 165us/sample - loss: 0.5516 - mse: 0.5516 - val_loss: 0.1141 - val_mse: 0.1141
Epoch 8/30
100/3021 [..............................] - ETA: 0s - loss: 0.5179 - mse: 0.5179
1400/3021 [============>.................] - ETA: 0s - loss: 0.5599 - mse: 0.5599
3021/3021 [==============================] - 0s 162us/sample - loss: 0.5366 - mse: 0.5366 - val_loss: 0.1125 - val_mse: 0.1125
Epoch 9/30
100/3021 [..............................] - ETA: 0s - loss: 0.6055 - mse: 0.6055
1500/3021 [=============>................] - ETA: 0s - loss: 0.5658 - mse: 0.5658
3021/3021 [==============================] - 1s 168us/sample - loss: 0.5635 - mse: 0.5635 - val_loss: 0.1975 - val_mse: 0.1975
Epoch 10/30
100/3021 [..............................] - ETA: 0s - loss: 0.4659 - mse: 0.4659
1600/3021 [==============>...............] - ETA: 0s - loss: 0.5185 - mse: 0.5185
3021/3021 [==============================] - 0s 159us/sample - loss: 0.5291 - mse: 0.5291 - val_loss: 0.1085 - val_mse: 0.1085
Epoch 11/30
100/3021 [..............................] - ETA: 0s - loss: 0.4535 - mse: 0.4535
1400/3021 [============>.................] - ETA: 0s - loss: 0.4570 - mse: 0.4570
3021/3021 [==============================] - 0s 160us/sample - loss: 0.4676 - mse: 0.4676 - val_loss: 0.0943 - val_mse: 0.0943
Epoch 12/30
100/3021 [..............................] - ETA: 0s - loss: 0.4298 - mse: 0.4298
1200/3021 [==========>...................] - ETA: 0s - loss: 0.4615 - mse: 0.4615
3021/3021 [==============================] - 0s 163us/sample - loss: 0.4648 - mse: 0.4648 - val_loss: 0.0961 - val_mse: 0.0961
Epoch 13/30
100/3021 [..............................] - ETA: 0s - loss: 0.4061 - mse: 0.4061
1500/3021 [=============>................] - ETA: 0s - loss: 0.4306 - mse: 0.4306
3021/3021 [==============================] - 0s 156us/sample - loss: 0.4374 - mse: 0.4374 - val_loss: 0.1349 - val_mse: 0.1349
Epoch 14/30
100/3021 [..............................] - ETA: 0s - loss: 0.6184 - mse: 0.6184
2500/3021 [=======================>......] - ETA: 0s - loss: 0.4511 - mse: 0.4511
3021/3021 [==============================] - 0s 149us/sample - loss: 0.4550 - mse: 0.4550 - val_loss: 0.0875 - val_mse: 0.0875
Epoch 15/30
100/3021 [..............................] - ETA: 0s - loss: 0.3827 - mse: 0.3827
2000/3021 [==================>...........] - ETA: 0s - loss: 0.4294 - mse: 0.4294
3021/3021 [==============================] - 0s 165us/sample - loss: 0.4298 - mse: 0.4298 - val_loss: 0.0900 - val_mse: 0.0900
Epoch 16/30
100/3021 [..............................] - ETA: 0s - loss: 0.3690 - mse: 0.3690
1100/3021 [=========>....................] - ETA: 0s - loss: 0.4265 - mse: 0.4265
3021/3021 [==============================] - 1s 167us/sample - loss: 0.4319 - mse: 0.4319 - val_loss: 0.0723 - val_mse: 0.0723
Epoch 17/30
100/3021 [..............................] - ETA: 0s - loss: 0.3700 - mse: 0.3700
1500/3021 [=============>................] - ETA: 0s - loss: 0.4054 - mse: 0.4054
3021/3021 [==============================] - 0s 160us/sample - loss: 0.4134 - mse: 0.4134 - val_loss: 0.0758 - val_mse: 0.0758
Epoch 18/30
100/3021 [..............................] - ETA: 0s - loss: 0.3991 - mse: 0.3991
2200/3021 [====================>.........] - ETA: 0s - loss: 0.3902 - mse: 0.3902
3021/3021 [==============================] - 0s 150us/sample - loss: 0.3852 - mse: 0.3852 - val_loss: 0.0738 - val_mse: 0.0738
Epoch 19/30
100/3021 [..............................] - ETA: 0s - loss: 0.4422 - mse: 0.4422
1100/3021 [=========>....................] - ETA: 0s - loss: 0.4085 - mse: 0.4085
3021/3021 [==============================] - 1s 169us/sample - loss: 0.4179 - mse: 0.4179 - val_loss: 0.1113 - val_mse: 0.1113
Epoch 20/30
100/3021 [..............................] - ETA: 0s - loss: 0.3720 - mse: 0.3720
1800/3021 [================>.............] - ETA: 0s - loss: 0.4104 - mse: 0.4104
3021/3021 [==============================] - 0s 150us/sample - loss: 0.4046 - mse: 0.4046 - val_loss: 0.0776 - val_mse: 0.0776
Epoch 21/30
100/3021 [..............................] - ETA: 0s - loss: 0.4080 - mse: 0.4080
2200/3021 [====================>.........] - ETA: 0s - loss: 0.3952 - mse: 0.3952
3021/3021 [==============================] - 0s 158us/sample - loss: 0.3942 - mse: 0.3942 - val_loss: 0.0742 - val_mse: 0.0742
Epoch 22/30
100/3021 [..............................] - ETA: 0s - loss: 0.3290 - mse: 0.3290
2000/3021 [==================>...........] - ETA: 0s - loss: 0.3971 - mse: 0.3971
3021/3021 [==============================] - 0s 160us/sample - loss: 0.3948 - mse: 0.3948 - val_loss: 0.0635 - val_mse: 0.0635
Epoch 23/30
100/3021 [..............................] - ETA: 0s - loss: 0.3694 - mse: 0.3694
1700/3021 [===============>..............] - ETA: 0s - loss: 0.3724 - mse: 0.3724
3021/3021 [==============================] - 0s 155us/sample - loss: 0.3726 - mse: 0.3726 - val_loss: 0.0655 - val_mse: 0.0655
Epoch 24/30
100/3021 [..............................] - ETA: 0s - loss: 0.4146 - mse: 0.4146
1700/3021 [===============>..............] - ETA: 0s - loss: 0.3878 - mse: 0.3878
3021/3021 [==============================] - 0s 160us/sample - loss: 0.3789 - mse: 0.3789 - val_loss: 0.0905 - val_mse: 0.0905
Epoch 25/30
100/3021 [..............................] - ETA: 0s - loss: 0.4124 - mse: 0.4124
1500/3021 [=============>................] - ETA: 0s - loss: 0.3893 - mse: 0.3893
3021/3021 [==============================] - 0s 154us/sample - loss: 0.3710 - mse: 0.3710 - val_loss: 0.0634 - val_mse: 0.0634
Epoch 26/30
100/3021 [..............................] - ETA: 0s - loss: 0.3760 - mse: 0.3760
2300/3021 [=====================>........] - ETA: 0s - loss: 0.3839 - mse: 0.3839
3021/3021 [==============================] - 0s 153us/sample - loss: 0.3839 - mse: 0.3839 - val_loss: 0.0897 - val_mse: 0.0897
Epoch 27/30
100/3021 [..............................] - ETA: 0s - loss: 0.3244 - mse: 0.3244
1700/3021 [===============>..............] - ETA: 0s - loss: 0.3636 - mse: 0.3636
3021/3021 [==============================] - 0s 153us/sample - loss: 0.3870 - mse: 0.3870 - val_loss: 0.1128 - val_mse: 0.1128
Epoch 28/30
100/3021 [..............................] - ETA: 0s - loss: 0.4591 - mse: 0.4591
2100/3021 [===================>..........] - ETA: 0s - loss: 0.3640 - mse: 0.3640
3021/3021 [==============================] - 0s 163us/sample - loss: 0.3668 - mse: 0.3668 - val_loss: 0.1162 - val_mse: 0.1162
Epoch 29/30
100/3021 [..............................] - ETA: 0s - loss: 0.5127 - mse: 0.5127
2000/3021 [==================>...........] - ETA: 0s - loss: 0.3955 - mse: 0.3955
3021/3021 [==============================] - 0s 162us/sample - loss: 0.3881 - mse: 0.3881 - val_loss: 0.0796 - val_mse: 0.0796
Epoch 30/30
100/3021 [..............................] - ETA: 0s - loss: 0.2876 - mse: 0.2876
1700/3021 [===============>..............] - ETA: 0s - loss: 0.3361 - mse: 0.3361
3021/3021 [==============================] - 1s 172us/sample - loss: 0.3382 - mse: 0.3382 - val_loss: 0.0609 - val_mse: 0.0609Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-05-04T01-07-42Z
Training run 32/46 (flags = list(64, 64, 1e-04, 200, 30, "tanh", "tanh", 0.05, 0.1))
Using run directory runs/2020-05-04T01-08-00Z
> FLAGS <- flags(
+ flag_numeric("nodes1", 128),
+ flag_numeric("nodes2", 128),
+ flag_numeric("batch_size", 100),
+ flag_string("activation1" .... [TRUNCATED]
> model = keras_model_sequential()
> model %>%
+ layer_dense(units=FLAGS$nodes1, activation=FLAGS$activation1, input_shape=dim(efw_train2)[2]) %>%
+ layer_dropout(FLAGS$dropout1) %> .... [TRUNCATED]
> model %>% compile(
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ loss = 'mse',
+ metrics = c('mse')
+ )
> model %>% fit(
+ as.matrix(efw_train2), train2Label,
+ epochs=FLAGS$epochs,
+ batch_size=FLAGS$batch_size,
+ validation_data=list(as.matrix( .... [TRUNCATED]
Train on 3021 samples, validate on 334 samples
Epoch 1/30
200/3021 [>.............................] - ETA: 3s - loss: 43.3913 - mse: 43.3913
3021/3021 [==============================] - 1s 238us/sample - loss: 44.1557 - mse: 44.1557 - val_loss: 43.7649 - val_mse: 43.7649
Epoch 2/30
200/3021 [>.............................] - ETA: 0s - loss: 43.4405 - mse: 43.4405
3021/3021 [==============================] - 0s 145us/sample - loss: 43.2838 - mse: 43.2838 - val_loss: 43.0468 - val_mse: 43.0468
Epoch 3/30
200/3021 [>.............................] - ETA: 0s - loss: 43.6626 - mse: 43.6626
3021/3021 [==============================] - 0s 147us/sample - loss: 42.5708 - mse: 42.5708 - val_loss: 42.3737 - val_mse: 42.3737
Epoch 4/30
200/3021 [>.............................] - ETA: 0s - loss: 42.8648 - mse: 42.8648
2600/3021 [========================>.....] - ETA: 0s - loss: 41.8538 - mse: 41.8538
3021/3021 [==============================] - 0s 150us/sample - loss: 41.8508 - mse: 41.8508 - val_loss: 41.7563 - val_mse: 41.7563
Epoch 5/30
200/3021 [>.............................] - ETA: 0s - loss: 41.4477 - mse: 41.4477
3021/3021 [==============================] - 0s 147us/sample - loss: 41.1768 - mse: 41.1768 - val_loss: 41.1727 - val_mse: 41.1727
Epoch 6/30
200/3021 [>.............................] - ETA: 0s - loss: 40.4977 - mse: 40.4977
3021/3021 [==============================] - 0s 136us/sample - loss: 40.5821 - mse: 40.5821 - val_loss: 40.6410 - val_mse: 40.6410
Epoch 7/30
200/3021 [>.............................] - ETA: 0s - loss: 40.3297 - mse: 40.3297
3021/3021 [==============================] - 0s 138us/sample - loss: 40.0317 - mse: 40.0317 - val_loss: 40.1283 - val_mse: 40.1283
Epoch 8/30
200/3021 [>.............................] - ETA: 0s - loss: 40.3044 - mse: 40.3044
3021/3021 [==============================] - 0s 135us/sample - loss: 39.5288 - mse: 39.5288 - val_loss: 39.6222 - val_mse: 39.6222
Epoch 9/30
200/3021 [>.............................] - ETA: 0s - loss: 39.4010 - mse: 39.4010
3021/3021 [==============================] - 0s 141us/sample - loss: 38.9991 - mse: 38.9991 - val_loss: 39.1235 - val_mse: 39.1235
Epoch 10/30
200/3021 [>.............................] - ETA: 0s - loss: 39.1038 - mse: 39.1038
3021/3021 [==============================] - 0s 145us/sample - loss: 38.5096 - mse: 38.5096 - val_loss: 38.6303 - val_mse: 38.6303
Epoch 11/30
200/3021 [>.............................] - ETA: 0s - loss: 38.3269 - mse: 38.3269
2600/3021 [========================>.....] - ETA: 0s - loss: 37.9975 - mse: 37.9975
3021/3021 [==============================] - 0s 154us/sample - loss: 37.9677 - mse: 37.9677 - val_loss: 38.1264 - val_mse: 38.1264
Epoch 12/30
200/3021 [>.............................] - ETA: 0s - loss: 36.7078 - mse: 36.7078
3021/3021 [==============================] - 0s 141us/sample - loss: 37.4651 - mse: 37.4651 - val_loss: 37.6062 - val_mse: 37.6062
Epoch 13/30
200/3021 [>.............................] - ETA: 0s - loss: 37.4067 - mse: 37.4067
3021/3021 [==============================] - 0s 135us/sample - loss: 36.9357 - mse: 36.9357 - val_loss: 37.0851 - val_mse: 37.0851
Epoch 14/30
200/3021 [>.............................] - ETA: 0s - loss: 37.1394 - mse: 37.1394
3021/3021 [==============================] - 0s 134us/sample - loss: 36.4555 - mse: 36.4555 - val_loss: 36.5661 - val_mse: 36.5661
Epoch 15/30
200/3021 [>.............................] - ETA: 0s - loss: 36.7671 - mse: 36.7671
3021/3021 [==============================] - 0s 138us/sample - loss: 35.8990 - mse: 35.8990 - val_loss: 36.0405 - val_mse: 36.0405
Epoch 16/30
200/3021 [>.............................] - ETA: 0s - loss: 35.6360 - mse: 35.6360
3021/3021 [==============================] - 0s 140us/sample - loss: 35.3488 - mse: 35.3488 - val_loss: 35.5132 - val_mse: 35.5132
Epoch 17/30
200/3021 [>.............................] - ETA: 0s - loss: 35.2947 - mse: 35.2947
3021/3021 [==============================] - 0s 131us/sample - loss: 34.8021 - mse: 34.8021 - val_loss: 34.9765 - val_mse: 34.9765
Epoch 18/30
200/3021 [>.............................] - ETA: 0s - loss: 34.2828 - mse: 34.2828
3021/3021 [==============================] - 0s 133us/sample - loss: 34.2435 - mse: 34.2435 - val_loss: 34.4177 - val_mse: 34.4177
Epoch 19/30
200/3021 [>.............................] - ETA: 0s - loss: 34.3423 - mse: 34.3423
3021/3021 [==============================] - 0s 134us/sample - loss: 33.7342 - mse: 33.7342 - val_loss: 33.8904 - val_mse: 33.8904
Epoch 20/30
200/3021 [>.............................] - ETA: 0s - loss: 33.3116 - mse: 33.3116
3021/3021 [==============================] - 0s 142us/sample - loss: 33.1272 - mse: 33.1272 - val_loss: 33.3472 - val_mse: 33.3472
Epoch 21/30
200/3021 [>.............................] - ETA: 0s - loss: 32.9445 - mse: 32.9445
3021/3021 [==============================] - 0s 140us/sample - loss: 32.5891 - mse: 32.5891 - val_loss: 32.7789 - val_mse: 32.7789
Epoch 22/30
200/3021 [>.............................] - ETA: 0s - loss: 31.7832 - mse: 31.7832
3021/3021 [==============================] - 0s 140us/sample - loss: 32.0221 - mse: 32.0221 - val_loss: 32.2243 - val_mse: 32.2243
Epoch 23/30
200/3021 [>.............................] - ETA: 0s - loss: 31.8026 - mse: 31.8026
2000/3021 [==================>...........] - ETA: 0s - loss: 31.5156 - mse: 31.5156
3021/3021 [==============================] - 0s 148us/sample - loss: 31.4495 - mse: 31.4495 - val_loss: 31.6641 - val_mse: 31.6641
Epoch 24/30
200/3021 [>.............................] - ETA: 0s - loss: 30.6886 - mse: 30.6886
3021/3021 [==============================] - 0s 140us/sample - loss: 30.8575 - mse: 30.8575 - val_loss: 31.0938 - val_mse: 31.0938
Epoch 25/30
200/3021 [>.............................] - ETA: 0s - loss: 30.4499 - mse: 30.4499
3021/3021 [==============================] - 0s 140us/sample - loss: 30.2215 - mse: 30.2215 - val_loss: 30.5146 - val_mse: 30.5146
Epoch 26/30
200/3021 [>.............................] - ETA: 0s - loss: 30.3940 - mse: 30.3940
3021/3021 [==============================] - 0s 130us/sample - loss: 29.6445 - mse: 29.6445 - val_loss: 29.9499 - val_mse: 29.9499
Epoch 27/30
200/3021 [>.............................] - ETA: 0s - loss: 29.4947 - mse: 29.4947
3021/3021 [==============================] - 0s 140us/sample - loss: 29.0465 - mse: 29.0465 - val_loss: 29.3520 - val_mse: 29.3520
Epoch 28/30
200/3021 [>.............................] - ETA: 0s - loss: 28.5910 - mse: 28.5910
3021/3021 [==============================] - 0s 142us/sample - loss: 28.4291 - mse: 28.4291 - val_loss: 28.7285 - val_mse: 28.7285
Epoch 29/30
200/3021 [>.............................] - ETA: 0s - loss: 28.9924 - mse: 28.9924
2600/3021 [========================>.....] - ETA: 0s - loss: 27.8650 - mse: 27.8650
3021/3021 [==============================] - 0s 139us/sample - loss: 27.8767 - mse: 27.8767 - val_loss: 28.1371 - val_mse: 28.1371
Epoch 30/30
200/3021 [>.............................] - ETA: 0s - loss: 27.7339 - mse: 27.7339
3021/3021 [==============================] - 0s 136us/sample - loss: 27.2317 - mse: 27.2317 - val_loss: 27.5363 - val_mse: 27.5363Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-05-04T01-08-00Z
Training run 33/46 (flags = list(64, 392, 0.05, 200, 30, "sigmoid", "tanh", 0.2, 0.5))
Using run directory runs/2020-05-04T01-08-17Z
> FLAGS <- flags(
+ flag_numeric("nodes1", 128),
+ flag_numeric("nodes2", 128),
+ flag_numeric("batch_size", 100),
+ flag_string("activation1" .... [TRUNCATED]
> model = keras_model_sequential()
> model %>%
+ layer_dense(units=FLAGS$nodes1, activation=FLAGS$activation1, input_shape=dim(efw_train2)[2]) %>%
+ layer_dropout(FLAGS$dropout1) %> .... [TRUNCATED]
> model %>% compile(
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ loss = 'mse',
+ metrics = c('mse')
+ )
> model %>% fit(
+ as.matrix(efw_train2), train2Label,
+ epochs=FLAGS$epochs,
+ batch_size=FLAGS$batch_size,
+ validation_data=list(as.matrix( .... [TRUNCATED]
Train on 3021 samples, validate on 334 samples
Epoch 1/30
200/3021 [>.............................] - ETA: 4s - loss: 32.1683 - mse: 32.1683
3021/3021 [==============================] - 1s 252us/sample - loss: 5.9860 - mse: 5.9860 - val_loss: 2.1528 - val_mse: 2.1528
Epoch 2/30
200/3021 [>.............................] - ETA: 0s - loss: 2.2753 - mse: 2.2753
3021/3021 [==============================] - 0s 145us/sample - loss: 1.1534 - mse: 1.1534 - val_loss: 0.2972 - val_mse: 0.2972
Epoch 3/30
200/3021 [>.............................] - ETA: 0s - loss: 0.6259 - mse: 0.6259
3021/3021 [==============================] - 0s 147us/sample - loss: 0.5434 - mse: 0.5434 - val_loss: 0.1677 - val_mse: 0.1677
Epoch 4/30
200/3021 [>.............................] - ETA: 0s - loss: 0.3938 - mse: 0.3938
3000/3021 [============================>.] - ETA: 0s - loss: 0.4154 - mse: 0.4154
3021/3021 [==============================] - 0s 142us/sample - loss: 0.4156 - mse: 0.4156 - val_loss: 0.1191 - val_mse: 0.1191
Epoch 5/30
200/3021 [>.............................] - ETA: 0s - loss: 0.4474 - mse: 0.4474
3021/3021 [==============================] - 0s 147us/sample - loss: 0.4029 - mse: 0.4029 - val_loss: 0.0926 - val_mse: 0.0926
Epoch 6/30
200/3021 [>.............................] - ETA: 0s - loss: 0.4100 - mse: 0.4100
3000/3021 [============================>.] - ETA: 0s - loss: 0.3843 - mse: 0.3843
3021/3021 [==============================] - 0s 146us/sample - loss: 0.3829 - mse: 0.3829 - val_loss: 0.0791 - val_mse: 0.0791
Epoch 7/30
200/3021 [>.............................] - ETA: 0s - loss: 0.3731 - mse: 0.3731
2600/3021 [========================>.....] - ETA: 0s - loss: 0.3697 - mse: 0.3697
3021/3021 [==============================] - 0s 150us/sample - loss: 0.3599 - mse: 0.3599 - val_loss: 0.0899 - val_mse: 0.0899
Epoch 8/30
200/3021 [>.............................] - ETA: 0s - loss: 0.3072 - mse: 0.3072
3021/3021 [==============================] - 0s 135us/sample - loss: 0.3399 - mse: 0.3399 - val_loss: 0.0906 - val_mse: 0.0906
Epoch 9/30
200/3021 [>.............................] - ETA: 0s - loss: 0.3325 - mse: 0.3325
3021/3021 [==============================] - 0s 135us/sample - loss: 0.3360 - mse: 0.3360 - val_loss: 0.0794 - val_mse: 0.0794
Epoch 10/30
200/3021 [>.............................] - ETA: 0s - loss: 0.2711 - mse: 0.2711
3021/3021 [==============================] - 0s 146us/sample - loss: 0.3243 - mse: 0.3243 - val_loss: 0.0660 - val_mse: 0.0660
Epoch 11/30
200/3021 [>.............................] - ETA: 0s - loss: 0.3342 - mse: 0.3342
3000/3021 [============================>.] - ETA: 0s - loss: 0.2956 - mse: 0.2956
3021/3021 [==============================] - 0s 148us/sample - loss: 0.2954 - mse: 0.2954 - val_loss: 0.0710 - val_mse: 0.0710
Epoch 12/30
200/3021 [>.............................] - ETA: 0s - loss: 0.3363 - mse: 0.3363
3021/3021 [==============================] - 0s 156us/sample - loss: 0.2978 - mse: 0.2978 - val_loss: 0.0642 - val_mse: 0.0642
Epoch 13/30
200/3021 [>.............................] - ETA: 0s - loss: 0.3531 - mse: 0.3531
3021/3021 [==============================] - 0s 138us/sample - loss: 0.2890 - mse: 0.2890 - val_loss: 0.0699 - val_mse: 0.0699
Epoch 14/30
200/3021 [>.............................] - ETA: 0s - loss: 0.2847 - mse: 0.2847
3021/3021 [==============================] - 0s 146us/sample - loss: 0.2959 - mse: 0.2959 - val_loss: 0.0677 - val_mse: 0.0677
Epoch 15/30
200/3021 [>.............................] - ETA: 0s - loss: 0.3043 - mse: 0.3043
3021/3021 [==============================] - 0s 140us/sample - loss: 0.2701 - mse: 0.2701 - val_loss: 0.0993 - val_mse: 0.0993
Epoch 16/30
200/3021 [>.............................] - ETA: 0s - loss: 0.2639 - mse: 0.2639
2200/3021 [====================>.........] - ETA: 0s - loss: 0.2688 - mse: 0.2688
3021/3021 [==============================] - 0s 162us/sample - loss: 0.2688 - mse: 0.2688 - val_loss: 0.0639 - val_mse: 0.0639
Epoch 17/30
200/3021 [>.............................] - ETA: 0s - loss: 0.2505 - mse: 0.2505
3021/3021 [==============================] - 0s 144us/sample - loss: 0.2597 - mse: 0.2597 - val_loss: 0.0600 - val_mse: 0.0600
Epoch 18/30
200/3021 [>.............................] - ETA: 0s - loss: 0.2286 - mse: 0.2286
2000/3021 [==================>...........] - ETA: 0s - loss: 0.2387 - mse: 0.2387
3021/3021 [==============================] - 0s 150us/sample - loss: 0.2450 - mse: 0.2450 - val_loss: 0.0740 - val_mse: 0.0740
Epoch 19/30
200/3021 [>.............................] - ETA: 0s - loss: 0.3129 - mse: 0.3129
3021/3021 [==============================] - 0s 130us/sample - loss: 0.2536 - mse: 0.2536 - val_loss: 0.0554 - val_mse: 0.0554
Epoch 20/30
200/3021 [>.............................] - ETA: 0s - loss: 0.2857 - mse: 0.2857
3021/3021 [==============================] - 0s 137us/sample - loss: 0.2387 - mse: 0.2387 - val_loss: 0.0875 - val_mse: 0.0875
Epoch 21/30
200/3021 [>.............................] - ETA: 0s - loss: 0.2858 - mse: 0.2858
3021/3021 [==============================] - 0s 148us/sample - loss: 0.2459 - mse: 0.2459 - val_loss: 0.0708 - val_mse: 0.0708
Epoch 22/30
200/3021 [>.............................] - ETA: 0s - loss: 0.2549 - mse: 0.2549
3000/3021 [============================>.] - ETA: 0s - loss: 0.2351 - mse: 0.2351
3021/3021 [==============================] - 0s 147us/sample - loss: 0.2351 - mse: 0.2351 - val_loss: 0.0638 - val_mse: 0.0638
Epoch 23/30
200/3021 [>.............................] - ETA: 0s - loss: 0.2317 - mse: 0.2317
3000/3021 [============================>.] - ETA: 0s - loss: 0.2374 - mse: 0.2374
3021/3021 [==============================] - 0s 141us/sample - loss: 0.2380 - mse: 0.2380 - val_loss: 0.0625 - val_mse: 0.0625
Epoch 24/30
200/3021 [>.............................] - ETA: 0s - loss: 0.2381 - mse: 0.2381
3021/3021 [==============================] - 0s 137us/sample - loss: 0.2246 - mse: 0.2246 - val_loss: 0.0644 - val_mse: 0.0644
Epoch 25/30
200/3021 [>.............................] - ETA: 0s - loss: 0.1679 - mse: 0.1679
2800/3021 [==========================>...] - ETA: 0s - loss: 0.2120 - mse: 0.2120
3021/3021 [==============================] - 0s 147us/sample - loss: 0.2133 - mse: 0.2133 - val_loss: 0.0896 - val_mse: 0.0896
Epoch 26/30
200/3021 [>.............................] - ETA: 0s - loss: 0.2525 - mse: 0.2525
3021/3021 [==============================] - 0s 138us/sample - loss: 0.2373 - mse: 0.2373 - val_loss: 0.0744 - val_mse: 0.0744
Epoch 27/30
200/3021 [>.............................] - ETA: 0s - loss: 0.2140 - mse: 0.2140
2800/3021 [==========================>...] - ETA: 0s - loss: 0.2115 - mse: 0.2115
3021/3021 [==============================] - 0s 143us/sample - loss: 0.2099 - mse: 0.2099 - val_loss: 0.0720 - val_mse: 0.0720
Epoch 28/30
200/3021 [>.............................] - ETA: 0s - loss: 0.2387 - mse: 0.2387
3021/3021 [==============================] - 0s 146us/sample - loss: 0.2124 - mse: 0.2124 - val_loss: 0.0562 - val_mse: 0.0562
Epoch 29/30
200/3021 [>.............................] - ETA: 0s - loss: 0.1726 - mse: 0.1726
3021/3021 [==============================] - 0s 143us/sample - loss: 0.1971 - mse: 0.1971 - val_loss: 0.0527 - val_mse: 0.0527
Epoch 30/30
200/3021 [>.............................] - ETA: 0s - loss: 0.1792 - mse: 0.1792
2000/3021 [==================>...........] - ETA: 0s - loss: 0.1902 - mse: 0.1902
3021/3021 [==============================] - 0s 152us/sample - loss: 0.1892 - mse: 0.1892 - val_loss: 0.0706 - val_mse: 0.0706Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-05-04T01-08-17Z
Training run 34/46 (flags = list(64, 128, 0.001, 100, 100, "tanh", "tanh", 0.05, 0.05))
Using run directory runs/2020-05-04T01-08-34Z
> FLAGS <- flags(
+ flag_numeric("nodes1", 128),
+ flag_numeric("nodes2", 128),
+ flag_numeric("batch_size", 100),
+ flag_string("activation1" .... [TRUNCATED]
> model = keras_model_sequential()
> model %>%
+ layer_dense(units=FLAGS$nodes1, activation=FLAGS$activation1, input_shape=dim(efw_train2)[2]) %>%
+ layer_dropout(FLAGS$dropout1) %> .... [TRUNCATED]
> model %>% compile(
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ loss = 'mse',
+ metrics = c('mse')
+ )
> model %>% fit(
+ as.matrix(efw_train2), train2Label,
+ epochs=FLAGS$epochs,
+ batch_size=FLAGS$batch_size,
+ validation_data=list(as.matrix( .... [TRUNCATED]
Train on 3021 samples, validate on 334 samples
Epoch 1/100
100/3021 [..............................] - ETA: 7s - loss: 43.7721 - mse: 43.7721
2200/3021 [====================>.........] - ETA: 0s - loss: 39.6332 - mse: 39.6332
3021/3021 [==============================] - 1s 252us/sample - loss: 38.2921 - mse: 38.2921 - val_loss: 33.6841 - val_mse: 33.6841
Epoch 2/100
100/3021 [..............................] - ETA: 0s - loss: 33.1394 - mse: 33.1394
2000/3021 [==================>...........] - ETA: 0s - loss: 30.0673 - mse: 30.0673
3021/3021 [==============================] - 0s 160us/sample - loss: 28.1588 - mse: 28.1588 - val_loss: 23.1711 - val_mse: 23.1711
Epoch 3/100
100/3021 [..............................] - ETA: 0s - loss: 23.0999 - mse: 23.0999
2400/3021 [======================>.......] - ETA: 0s - loss: 18.3023 - mse: 18.3023
3021/3021 [==============================] - 0s 163us/sample - loss: 17.2749 - mse: 17.2749 - val_loss: 12.4306 - val_mse: 12.4306
Epoch 4/100
100/3021 [..............................] - ETA: 0s - loss: 12.2440 - mse: 12.2440
2000/3021 [==================>...........] - ETA: 0s - loss: 9.0421 - mse: 9.0421
3021/3021 [==============================] - 0s 159us/sample - loss: 7.9046 - mse: 7.9046 - val_loss: 4.7067 - val_mse: 4.7067
Epoch 5/100
100/3021 [..............................] - ETA: 0s - loss: 3.7939 - mse: 3.7939
2300/3021 [=====================>........] - ETA: 0s - loss: 2.8048 - mse: 2.8048
3021/3021 [==============================] - 0s 160us/sample - loss: 2.4502 - mse: 2.4502 - val_loss: 1.2084 - val_mse: 1.2084
Epoch 6/100
100/3021 [..............................] - ETA: 0s - loss: 1.1635 - mse: 1.1635
1400/3021 [============>.................] - ETA: 0s - loss: 0.7250 - mse: 0.7250
3021/3021 [==============================] - 0s 158us/sample - loss: 0.5660 - mse: 0.5660 - val_loss: 0.2894 - val_mse: 0.2894
Epoch 7/100
100/3021 [..............................] - ETA: 0s - loss: 0.2431 - mse: 0.2431
2700/3021 [=========================>....] - ETA: 0s - loss: 0.1988 - mse: 0.1988
3021/3021 [==============================] - 1s 166us/sample - loss: 0.1914 - mse: 0.1914 - val_loss: 0.1352 - val_mse: 0.1352
Epoch 8/100
100/3021 [..............................] - ETA: 0s - loss: 0.1884 - mse: 0.1884
2600/3021 [========================>.....] - ETA: 0s - loss: 0.1522 - mse: 0.1522
3021/3021 [==============================] - 0s 153us/sample - loss: 0.1509 - mse: 0.1509 - val_loss: 0.1054 - val_mse: 0.1054
Epoch 9/100
100/3021 [..............................] - ETA: 0s - loss: 0.1089 - mse: 0.1089
2100/3021 [===================>..........] - ETA: 0s - loss: 0.1445 - mse: 0.1445
3021/3021 [==============================] - 0s 160us/sample - loss: 0.1382 - mse: 0.1382 - val_loss: 0.0924 - val_mse: 0.0924
Epoch 10/100
100/3021 [..............................] - ETA: 0s - loss: 0.1947 - mse: 0.1947
1300/3021 [===========>..................] - ETA: 0s - loss: 0.1277 - mse: 0.1277
3021/3021 [==============================] - 0s 163us/sample - loss: 0.1249 - mse: 0.1249 - val_loss: 0.0775 - val_mse: 0.0775
Epoch 11/100
100/3021 [..............................] - ETA: 0s - loss: 0.1206 - mse: 0.1206
1300/3021 [===========>..................] - ETA: 0s - loss: 0.1180 - mse: 0.1180
3021/3021 [==============================] - 0s 160us/sample - loss: 0.1117 - mse: 0.1117 - val_loss: 0.0696 - val_mse: 0.0696
Epoch 12/100
100/3021 [..............................] - ETA: 0s - loss: 0.1006 - mse: 0.1006
1300/3021 [===========>..................] - ETA: 0s - loss: 0.1061 - mse: 0.1061
3021/3021 [==============================] - 0s 158us/sample - loss: 0.1093 - mse: 0.1093 - val_loss: 0.0657 - val_mse: 0.0657
Epoch 13/100
100/3021 [..............................] - ETA: 0s - loss: 0.1020 - mse: 0.1020
2600/3021 [========================>.....] - ETA: 0s - loss: 0.1039 - mse: 0.1039
3021/3021 [==============================] - 0s 156us/sample - loss: 0.1042 - mse: 0.1042 - val_loss: 0.0608 - val_mse: 0.0608
Epoch 14/100
100/3021 [..............................] - ETA: 0s - loss: 0.1035 - mse: 0.1035
2200/3021 [====================>.........] - ETA: 0s - loss: 0.1007 - mse: 0.1007
3021/3021 [==============================] - 0s 153us/sample - loss: 0.1019 - mse: 0.1019 - val_loss: 0.0564 - val_mse: 0.0564
Epoch 15/100
100/3021 [..............................] - ETA: 0s - loss: 0.1561 - mse: 0.1561
2600/3021 [========================>.....] - ETA: 0s - loss: 0.1024 - mse: 0.1024
3021/3021 [==============================] - 0s 159us/sample - loss: 0.1017 - mse: 0.1017 - val_loss: 0.0541 - val_mse: 0.0541
Epoch 16/100
100/3021 [..............................] - ETA: 0s - loss: 0.1197 - mse: 0.1197
1300/3021 [===========>..................] - ETA: 0s - loss: 0.0963 - mse: 0.0963
3021/3021 [==============================] - 0s 165us/sample - loss: 0.0986 - mse: 0.0986 - val_loss: 0.0539 - val_mse: 0.0539
Epoch 17/100
100/3021 [..............................] - ETA: 0s - loss: 0.1098 - mse: 0.1098
1600/3021 [==============>...............] - ETA: 0s - loss: 0.1059 - mse: 0.1059
3021/3021 [==============================] - 1s 167us/sample - loss: 0.0969 - mse: 0.0969 - val_loss: 0.0524 - val_mse: 0.0524
Epoch 18/100
100/3021 [..............................] - ETA: 0s - loss: 0.0922 - mse: 0.0922
1800/3021 [================>.............] - ETA: 0s - loss: 0.0975 - mse: 0.0975
3021/3021 [==============================] - 0s 154us/sample - loss: 0.0955 - mse: 0.0955 - val_loss: 0.0572 - val_mse: 0.0572
Epoch 19/100
100/3021 [..............................] - ETA: 0s - loss: 0.1302 - mse: 0.1302
2500/3021 [=======================>......] - ETA: 0s - loss: 0.0950 - mse: 0.0950
3021/3021 [==============================] - 0s 157us/sample - loss: 0.0944 - mse: 0.0944 - val_loss: 0.0516 - val_mse: 0.0516
Epoch 20/100
100/3021 [..............................] - ETA: 0s - loss: 0.1038 - mse: 0.1038
1500/3021 [=============>................] - ETA: 0s - loss: 0.0967 - mse: 0.0967
3021/3021 [==============================] - 0s 150us/sample - loss: 0.0931 - mse: 0.0931 - val_loss: 0.0488 - val_mse: 0.0488
Epoch 21/100
100/3021 [..............................] - ETA: 0s - loss: 0.0810 - mse: 0.0810
2700/3021 [=========================>....] - ETA: 0s - loss: 0.0866 - mse: 0.0866
3021/3021 [==============================] - 0s 150us/sample - loss: 0.0867 - mse: 0.0867 - val_loss: 0.0477 - val_mse: 0.0477
Epoch 22/100
100/3021 [..............................] - ETA: 0s - loss: 0.0767 - mse: 0.0767
2600/3021 [========================>.....] - ETA: 0s - loss: 0.0917 - mse: 0.0917
3021/3021 [==============================] - 0s 153us/sample - loss: 0.0899 - mse: 0.0899 - val_loss: 0.0458 - val_mse: 0.0458
Epoch 23/100
100/3021 [..............................] - ETA: 0s - loss: 0.0723 - mse: 0.0723
2500/3021 [=======================>......] - ETA: 0s - loss: 0.0878 - mse: 0.0878
3021/3021 [==============================] - 0s 151us/sample - loss: 0.0884 - mse: 0.0884 - val_loss: 0.0458 - val_mse: 0.0458
Epoch 24/100
100/3021 [..............................] - ETA: 0s - loss: 0.0797 - mse: 0.0797
2600/3021 [========================>.....] - ETA: 0s - loss: 0.0885 - mse: 0.0885
3021/3021 [==============================] - 0s 155us/sample - loss: 0.0884 - mse: 0.0884 - val_loss: 0.0485 - val_mse: 0.0485
Epoch 25/100
100/3021 [..............................] - ETA: 0s - loss: 0.1238 - mse: 0.1238
1600/3021 [==============>...............] - ETA: 0s - loss: 0.0900 - mse: 0.0900
3021/3021 [==============================] - 0s 155us/sample - loss: 0.0912 - mse: 0.0912 - val_loss: 0.0440 - val_mse: 0.0440
Epoch 26/100
100/3021 [..............................] - ETA: 0s - loss: 0.0762 - mse: 0.0762
2600/3021 [========================>.....] - ETA: 0s - loss: 0.0868 - mse: 0.0868
3021/3021 [==============================] - 0s 155us/sample - loss: 0.0856 - mse: 0.0856 - val_loss: 0.0441 - val_mse: 0.0441
Epoch 27/100
100/3021 [..............................] - ETA: 0s - loss: 0.1041 - mse: 0.1041
1200/3021 [==========>...................] - ETA: 0s - loss: 0.0871 - mse: 0.0871
3021/3021 [==============================] - 0s 152us/sample - loss: 0.0847 - mse: 0.0847 - val_loss: 0.0437 - val_mse: 0.0437
Epoch 28/100
100/3021 [..............................] - ETA: 0s - loss: 0.0691 - mse: 0.0691
2300/3021 [=====================>........] - ETA: 0s - loss: 0.0923 - mse: 0.0923
3021/3021 [==============================] - 0s 151us/sample - loss: 0.0899 - mse: 0.0899 - val_loss: 0.0445 - val_mse: 0.0445
Epoch 29/100
100/3021 [..............................] - ETA: 0s - loss: 0.0919 - mse: 0.0919
2200/3021 [====================>.........] - ETA: 0s - loss: 0.0885 - mse: 0.0885
3021/3021 [==============================] - 0s 151us/sample - loss: 0.0858 - mse: 0.0858 - val_loss: 0.0440 - val_mse: 0.0440
Epoch 30/100
100/3021 [..............................] - ETA: 0s - loss: 0.0847 - mse: 0.0847
2500/3021 [=======================>......] - ETA: 0s - loss: 0.0872 - mse: 0.0872
3021/3021 [==============================] - 0s 159us/sample - loss: 0.0846 - mse: 0.0846 - val_loss: 0.0438 - val_mse: 0.0438
Epoch 31/100
100/3021 [..............................] - ETA: 0s - loss: 0.0720 - mse: 0.0720
1200/3021 [==========>...................] - ETA: 0s - loss: 0.0821 - mse: 0.0821
3021/3021 [==============================] - 0s 161us/sample - loss: 0.0827 - mse: 0.0827 - val_loss: 0.0426 - val_mse: 0.0426
Epoch 32/100
100/3021 [..............................] - ETA: 0s - loss: 0.0662 - mse: 0.0662
1300/3021 [===========>..................] - ETA: 0s - loss: 0.0787 - mse: 0.0787
3021/3021 [==============================] - 0s 154us/sample - loss: 0.0839 - mse: 0.0839 - val_loss: 0.0422 - val_mse: 0.0422
Epoch 33/100
100/3021 [..............................] - ETA: 0s - loss: 0.0900 - mse: 0.0900
2500/3021 [=======================>......] - ETA: 0s - loss: 0.0835 - mse: 0.0835
3021/3021 [==============================] - 0s 141us/sample - loss: 0.0847 - mse: 0.0847 - val_loss: 0.0415 - val_mse: 0.0415
Epoch 34/100
100/3021 [..............................] - ETA: 0s - loss: 0.0686 - mse: 0.0686
2300/3021 [=====================>........] - ETA: 0s - loss: 0.0816 - mse: 0.0816
3021/3021 [==============================] - 1s 173us/sample - loss: 0.0807 - mse: 0.0807 - val_loss: 0.0424 - val_mse: 0.0424
Epoch 35/100
100/3021 [..............................] - ETA: 0s - loss: 0.0701 - mse: 0.0701
1900/3021 [=================>............] - ETA: 0s - loss: 0.0819 - mse: 0.0819
3021/3021 [==============================] - 0s 164us/sample - loss: 0.0838 - mse: 0.0838 - val_loss: 0.0444 - val_mse: 0.0444
Epoch 36/100
100/3021 [..............................] - ETA: 0s - loss: 0.1142 - mse: 0.1142
1600/3021 [==============>...............] - ETA: 0s - loss: 0.0934 - mse: 0.0934
3021/3021 [==============================] - 0s 161us/sample - loss: 0.0880 - mse: 0.0880 - val_loss: 0.0418 - val_mse: 0.0418
Epoch 37/100
100/3021 [..............................] - ETA: 0s - loss: 0.0688 - mse: 0.0688
2100/3021 [===================>..........] - ETA: 0s - loss: 0.0828 - mse: 0.0828
3021/3021 [==============================] - 0s 154us/sample - loss: 0.0832 - mse: 0.0832 - val_loss: 0.0427 - val_mse: 0.0427
Epoch 38/100
100/3021 [..............................] - ETA: 0s - loss: 0.0834 - mse: 0.0834
2900/3021 [===========================>..] - ETA: 0s - loss: 0.0803 - mse: 0.0803
3021/3021 [==============================] - 0s 153us/sample - loss: 0.0817 - mse: 0.0817 - val_loss: 0.0408 - val_mse: 0.0408
Epoch 39/100
100/3021 [..............................] - ETA: 0s - loss: 0.0592 - mse: 0.0592
2700/3021 [=========================>....] - ETA: 0s - loss: 0.0803 - mse: 0.0803
3021/3021 [==============================] - 0s 147us/sample - loss: 0.0800 - mse: 0.0800 - val_loss: 0.0440 - val_mse: 0.0440
Epoch 40/100
100/3021 [..............................] - ETA: 0s - loss: 0.0651 - mse: 0.0651
2800/3021 [==========================>...] - ETA: 0s - loss: 0.0817 - mse: 0.0817
3021/3021 [==============================] - 0s 151us/sample - loss: 0.0808 - mse: 0.0808 - val_loss: 0.0434 - val_mse: 0.0434
Epoch 41/100
100/3021 [..............................] - ETA: 0s - loss: 0.0542 - mse: 0.0542
2200/3021 [====================>.........] - ETA: 0s - loss: 0.0838 - mse: 0.0838
3021/3021 [==============================] - 0s 156us/sample - loss: 0.0824 - mse: 0.0824 - val_loss: 0.0438 - val_mse: 0.0438
Epoch 42/100
100/3021 [..............................] - ETA: 0s - loss: 0.0851 - mse: 0.0851
1600/3021 [==============>...............] - ETA: 0s - loss: 0.0816 - mse: 0.0816
3021/3021 [==============================] - 0s 156us/sample - loss: 0.0782 - mse: 0.0782 - val_loss: 0.0430 - val_mse: 0.0430
Epoch 43/100
100/3021 [..............................] - ETA: 0s - loss: 0.0607 - mse: 0.0607
2700/3021 [=========================>....] - ETA: 0s - loss: 0.0803 - mse: 0.0803
3021/3021 [==============================] - 0s 161us/sample - loss: 0.0792 - mse: 0.0792 - val_loss: 0.0414 - val_mse: 0.0414
Epoch 44/100
100/3021 [..............................] - ETA: 0s - loss: 0.0847 - mse: 0.0847
1700/3021 [===============>..............] - ETA: 0s - loss: 0.0740 - mse: 0.0740
3021/3021 [==============================] - 0s 154us/sample - loss: 0.0778 - mse: 0.0778 - val_loss: 0.0450 - val_mse: 0.0450
Epoch 45/100
100/3021 [..............................] - ETA: 0s - loss: 0.0674 - mse: 0.0674
1200/3021 [==========>...................] - ETA: 0s - loss: 0.0746 - mse: 0.0746
3021/3021 [==============================] - 0s 165us/sample - loss: 0.0772 - mse: 0.0772 - val_loss: 0.0392 - val_mse: 0.0392
Epoch 46/100
100/3021 [..............................] - ETA: 0s - loss: 0.0916 - mse: 0.0916
1200/3021 [==========>...................] - ETA: 0s - loss: 0.0753 - mse: 0.0753
3021/3021 [==============================] - 0s 161us/sample - loss: 0.0760 - mse: 0.0760 - val_loss: 0.0387 - val_mse: 0.0387
Epoch 47/100
100/3021 [..............................] - ETA: 0s - loss: 0.0792 - mse: 0.0792
1900/3021 [=================>............] - ETA: 0s - loss: 0.0827 - mse: 0.0827
3021/3021 [==============================] - 0s 153us/sample - loss: 0.0819 - mse: 0.0819 - val_loss: 0.0401 - val_mse: 0.0401
Epoch 48/100
100/3021 [..............................] - ETA: 0s - loss: 0.0717 - mse: 0.0717
2400/3021 [======================>.......] - ETA: 0s - loss: 0.0814 - mse: 0.0814
3021/3021 [==============================] - 0s 153us/sample - loss: 0.0810 - mse: 0.0810 - val_loss: 0.0403 - val_mse: 0.0403
Epoch 49/100
100/3021 [..............................] - ETA: 0s - loss: 0.0862 - mse: 0.0862
1800/3021 [================>.............] - ETA: 0s - loss: 0.0773 - mse: 0.0773
3021/3021 [==============================] - 1s 168us/sample - loss: 0.0773 - mse: 0.0773 - val_loss: 0.0415 - val_mse: 0.0415
Epoch 50/100
100/3021 [..............................] - ETA: 0s - loss: 0.0577 - mse: 0.0577
1300/3021 [===========>..................] - ETA: 0s - loss: 0.0828 - mse: 0.0828
3021/3021 [==============================] - 0s 158us/sample - loss: 0.0823 - mse: 0.0823 - val_loss: 0.0400 - val_mse: 0.0400
Epoch 51/100
100/3021 [..............................] - ETA: 0s - loss: 0.0706 - mse: 0.0706
1800/3021 [================>.............] - ETA: 0s - loss: 0.0786 - mse: 0.0786
3021/3021 [==============================] - 0s 154us/sample - loss: 0.0774 - mse: 0.0774 - val_loss: 0.0406 - val_mse: 0.0406
Epoch 52/100
100/3021 [..............................] - ETA: 0s - loss: 0.0619 - mse: 0.0619
1800/3021 [================>.............] - ETA: 0s - loss: 0.0758 - mse: 0.0758
3021/3021 [==============================] - 0s 151us/sample - loss: 0.0765 - mse: 0.0765 - val_loss: 0.0379 - val_mse: 0.0379
Epoch 53/100
100/3021 [..............................] - ETA: 0s - loss: 0.0498 - mse: 0.0498
2700/3021 [=========================>....] - ETA: 0s - loss: 0.0803 - mse: 0.0803
3021/3021 [==============================] - 0s 149us/sample - loss: 0.0807 - mse: 0.0807 - val_loss: 0.0402 - val_mse: 0.0402
Epoch 54/100
100/3021 [..............................] - ETA: 0s - loss: 0.0753 - mse: 0.0753
2700/3021 [=========================>....] - ETA: 0s - loss: 0.0761 - mse: 0.0761
3021/3021 [==============================] - 0s 152us/sample - loss: 0.0759 - mse: 0.0759 - val_loss: 0.0370 - val_mse: 0.0370
Epoch 55/100
100/3021 [..............................] - ETA: 0s - loss: 0.0588 - mse: 0.0588
1200/3021 [==========>...................] - ETA: 0s - loss: 0.0750 - mse: 0.0750
3021/3021 [==============================] - 1s 180us/sample - loss: 0.0756 - mse: 0.0756 - val_loss: 0.0448 - val_mse: 0.0448
Epoch 56/100
100/3021 [..............................] - ETA: 0s - loss: 0.0691 - mse: 0.0691
2600/3021 [========================>.....] - ETA: 0s - loss: 0.0746 - mse: 0.0746
3021/3021 [==============================] - 0s 153us/sample - loss: 0.0744 - mse: 0.0744 - val_loss: 0.0376 - val_mse: 0.0376
Epoch 57/100
100/3021 [..............................] - ETA: 0s - loss: 0.0615 - mse: 0.0615
1800/3021 [================>.............] - ETA: 0s - loss: 0.0730 - mse: 0.0730
3021/3021 [==============================] - 0s 152us/sample - loss: 0.0768 - mse: 0.0768 - val_loss: 0.0397 - val_mse: 0.0397
Epoch 58/100
100/3021 [..............................] - ETA: 0s - loss: 0.0694 - mse: 0.0694
2800/3021 [==========================>...] - ETA: 0s - loss: 0.0718 - mse: 0.0718
3021/3021 [==============================] - 0s 152us/sample - loss: 0.0730 - mse: 0.0730 - val_loss: 0.0401 - val_mse: 0.0401
Epoch 59/100
100/3021 [..............................] - ETA: 0s - loss: 0.0888 - mse: 0.0888
1700/3021 [===============>..............] - ETA: 0s - loss: 0.0775 - mse: 0.0775
3021/3021 [==============================] - 0s 155us/sample - loss: 0.0759 - mse: 0.0759 - val_loss: 0.0414 - val_mse: 0.0414
Epoch 60/100
100/3021 [..............................] - ETA: 0s - loss: 0.0742 - mse: 0.0742
2700/3021 [=========================>....] - ETA: 0s - loss: 0.0762 - mse: 0.0762
3021/3021 [==============================] - 0s 146us/sample - loss: 0.0759 - mse: 0.0759 - val_loss: 0.0400 - val_mse: 0.0400
Epoch 61/100
100/3021 [..............................] - ETA: 0s - loss: 0.1270 - mse: 0.1270
2500/3021 [=======================>......] - ETA: 0s - loss: 0.0694 - mse: 0.0694
3021/3021 [==============================] - 0s 149us/sample - loss: 0.0696 - mse: 0.0696 - val_loss: 0.0375 - val_mse: 0.0375
Epoch 62/100
100/3021 [..............................] - ETA: 0s - loss: 0.0338 - mse: 0.0338
2600/3021 [========================>.....] - ETA: 0s - loss: 0.0765 - mse: 0.0765
3021/3021 [==============================] - 0s 153us/sample - loss: 0.0764 - mse: 0.0764 - val_loss: 0.0423 - val_mse: 0.0423
Epoch 63/100
100/3021 [..............................] - ETA: 0s - loss: 0.0632 - mse: 0.0632
1500/3021 [=============>................] - ETA: 0s - loss: 0.0779 - mse: 0.0779
3021/3021 [==============================] - 0s 160us/sample - loss: 0.0767 - mse: 0.0767 - val_loss: 0.0385 - val_mse: 0.0385
Epoch 64/100
100/3021 [..............................] - ETA: 0s - loss: 0.0766 - mse: 0.0766
2300/3021 [=====================>........] - ETA: 0s - loss: 0.0730 - mse: 0.0730
3021/3021 [==============================] - 0s 163us/sample - loss: 0.0731 - mse: 0.0731 - val_loss: 0.0400 - val_mse: 0.0400
Epoch 65/100
100/3021 [..............................] - ETA: 0s - loss: 0.0420 - mse: 0.0420
1200/3021 [==========>...................] - ETA: 0s - loss: 0.0695 - mse: 0.0695
3021/3021 [==============================] - 0s 162us/sample - loss: 0.0697 - mse: 0.0697 - val_loss: 0.0364 - val_mse: 0.0364
Epoch 66/100
100/3021 [..............................] - ETA: 0s - loss: 0.0754 - mse: 0.0754
1900/3021 [=================>............] - ETA: 0s - loss: 0.0770 - mse: 0.0770
3021/3021 [==============================] - 0s 151us/sample - loss: 0.0744 - mse: 0.0744 - val_loss: 0.0376 - val_mse: 0.0376
Epoch 67/100
100/3021 [..............................] - ETA: 0s - loss: 0.0604 - mse: 0.0604
2400/3021 [======================>.......] - ETA: 0s - loss: 0.0728 - mse: 0.0728
3021/3021 [==============================] - 0s 147us/sample - loss: 0.0735 - mse: 0.0735 - val_loss: 0.0345 - val_mse: 0.0345
Epoch 68/100
100/3021 [..............................] - ETA: 0s - loss: 0.0646 - mse: 0.0646
2300/3021 [=====================>........] - ETA: 0s - loss: 0.0692 - mse: 0.0692
3021/3021 [==============================] - 1s 167us/sample - loss: 0.0708 - mse: 0.0708 - val_loss: 0.0450 - val_mse: 0.0450
Epoch 69/100
100/3021 [..............................] - ETA: 0s - loss: 0.0596 - mse: 0.0596
1800/3021 [================>.............] - ETA: 0s - loss: 0.0738 - mse: 0.0738
3021/3021 [==============================] - 0s 161us/sample - loss: 0.0724 - mse: 0.0724 - val_loss: 0.0417 - val_mse: 0.0417
Epoch 70/100
100/3021 [..............................] - ETA: 0s - loss: 0.0677 - mse: 0.0677
2300/3021 [=====================>........] - ETA: 0s - loss: 0.0734 - mse: 0.0734
3021/3021 [==============================] - 0s 157us/sample - loss: 0.0732 - mse: 0.0732 - val_loss: 0.0397 - val_mse: 0.0397
Epoch 71/100
100/3021 [..............................] - ETA: 0s - loss: 0.0801 - mse: 0.0801
2100/3021 [===================>..........] - ETA: 0s - loss: 0.0753 - mse: 0.0753
3021/3021 [==============================] - 0s 151us/sample - loss: 0.0736 - mse: 0.0736 - val_loss: 0.0366 - val_mse: 0.0366
Epoch 72/100
100/3021 [..............................] - ETA: 0s - loss: 0.0776 - mse: 0.0776
1300/3021 [===========>..................] - ETA: 0s - loss: 0.0703 - mse: 0.0703
3021/3021 [==============================] - 0s 161us/sample - loss: 0.0702 - mse: 0.0702 - val_loss: 0.0383 - val_mse: 0.0383
Epoch 73/100
100/3021 [..............................] - ETA: 0s - loss: 0.0837 - mse: 0.0837
2500/3021 [=======================>......] - ETA: 0s - loss: 0.0748 - mse: 0.0748
3021/3021 [==============================] - 0s 150us/sample - loss: 0.0739 - mse: 0.0739 - val_loss: 0.0418 - val_mse: 0.0418
Epoch 74/100
100/3021 [..............................] - ETA: 0s - loss: 0.0793 - mse: 0.0793
2300/3021 [=====================>........] - ETA: 0s - loss: 0.0721 - mse: 0.0721
3021/3021 [==============================] - 0s 151us/sample - loss: 0.0714 - mse: 0.0714 - val_loss: 0.0378 - val_mse: 0.0378
Epoch 75/100
100/3021 [..............................] - ETA: 0s - loss: 0.0689 - mse: 0.0689
2400/3021 [======================>.......] - ETA: 0s - loss: 0.0692 - mse: 0.0692
3021/3021 [==============================] - 0s 156us/sample - loss: 0.0703 - mse: 0.0703 - val_loss: 0.0404 - val_mse: 0.0404
Epoch 76/100
100/3021 [..............................] - ETA: 0s - loss: 0.0718 - mse: 0.0718
1600/3021 [==============>...............] - ETA: 0s - loss: 0.0735 - mse: 0.0735
3021/3021 [==============================] - 0s 155us/sample - loss: 0.0704 - mse: 0.0704 - val_loss: 0.0388 - val_mse: 0.0388
Epoch 77/100
100/3021 [..............................] - ETA: 0s - loss: 0.0827 - mse: 0.0827
2800/3021 [==========================>...] - ETA: 0s - loss: 0.0670 - mse: 0.0670
3021/3021 [==============================] - 0s 148us/sample - loss: 0.0691 - mse: 0.0691 - val_loss: 0.0393 - val_mse: 0.0393
Epoch 78/100
100/3021 [..............................] - ETA: 0s - loss: 0.0703 - mse: 0.0703
1600/3021 [==============>...............] - ETA: 0s - loss: 0.0732 - mse: 0.0732
3021/3021 [==============================] - 0s 149us/sample - loss: 0.0685 - mse: 0.0685 - val_loss: 0.0393 - val_mse: 0.0393
Epoch 79/100
100/3021 [..............................] - ETA: 0s - loss: 0.0957 - mse: 0.0957
2400/3021 [======================>.......] - ETA: 0s - loss: 0.0700 - mse: 0.0700
3021/3021 [==============================] - 0s 155us/sample - loss: 0.0682 - mse: 0.0682 - val_loss: 0.0396 - val_mse: 0.0396
Epoch 80/100
100/3021 [..............................] - ETA: 0s - loss: 0.0697 - mse: 0.0697
2400/3021 [======================>.......] - ETA: 0s - loss: 0.0705 - mse: 0.0705
3021/3021 [==============================] - 0s 150us/sample - loss: 0.0691 - mse: 0.0691 - val_loss: 0.0385 - val_mse: 0.0385
Epoch 81/100
100/3021 [..............................] - ETA: 0s - loss: 0.0504 - mse: 0.0504
2400/3021 [======================>.......] - ETA: 0s - loss: 0.0662 - mse: 0.0662
3021/3021 [==============================] - 0s 161us/sample - loss: 0.0665 - mse: 0.0665 - val_loss: 0.0386 - val_mse: 0.0386
Epoch 82/100
100/3021 [..............................] - ETA: 0s - loss: 0.0507 - mse: 0.0507
1300/3021 [===========>..................] - ETA: 0s - loss: 0.0592 - mse: 0.0592
3021/3021 [==============================] - 0s 159us/sample - loss: 0.0687 - mse: 0.0687 - val_loss: 0.0387 - val_mse: 0.0387
Epoch 83/100
100/3021 [..............................] - ETA: 0s - loss: 0.0656 - mse: 0.0656
2100/3021 [===================>..........] - ETA: 0s - loss: 0.0698 - mse: 0.0698
3021/3021 [==============================] - 0s 148us/sample - loss: 0.0699 - mse: 0.0699 - val_loss: 0.0419 - val_mse: 0.0419
Epoch 84/100
100/3021 [..............................] - ETA: 0s - loss: 0.0645 - mse: 0.0645
2600/3021 [========================>.....] - ETA: 0s - loss: 0.0724 - mse: 0.0724
3021/3021 [==============================] - 0s 145us/sample - loss: 0.0741 - mse: 0.0741 - val_loss: 0.0475 - val_mse: 0.0475
Epoch 85/100
100/3021 [..............................] - ETA: 0s - loss: 0.0552 - mse: 0.0552
2200/3021 [====================>.........] - ETA: 0s - loss: 0.0700 - mse: 0.0700
3021/3021 [==============================] - 0s 160us/sample - loss: 0.0699 - mse: 0.0699 - val_loss: 0.0412 - val_mse: 0.0412
Epoch 86/100
100/3021 [..............................] - ETA: 0s - loss: 0.0597 - mse: 0.0597
1400/3021 [============>.................] - ETA: 0s - loss: 0.0692 - mse: 0.0692
3021/3021 [==============================] - 0s 160us/sample - loss: 0.0663 - mse: 0.0663 - val_loss: 0.0362 - val_mse: 0.0362
Epoch 87/100
100/3021 [..............................] - ETA: 0s - loss: 0.0439 - mse: 0.0439
1900/3021 [=================>............] - ETA: 0s - loss: 0.0664 - mse: 0.0664
3021/3021 [==============================] - 0s 152us/sample - loss: 0.0659 - mse: 0.0659 - val_loss: 0.0374 - val_mse: 0.0374
Epoch 88/100
100/3021 [..............................] - ETA: 0s - loss: 0.0708 - mse: 0.0708
2700/3021 [=========================>....] - ETA: 0s - loss: 0.0677 - mse: 0.0677
3021/3021 [==============================] - 0s 152us/sample - loss: 0.0664 - mse: 0.0664 - val_loss: 0.0376 - val_mse: 0.0376
Epoch 89/100
100/3021 [..............................] - ETA: 0s - loss: 0.0701 - mse: 0.0701
1200/3021 [==========>...................] - ETA: 0s - loss: 0.0678 - mse: 0.0678
3021/3021 [==============================] - 0s 162us/sample - loss: 0.0692 - mse: 0.0692 - val_loss: 0.0418 - val_mse: 0.0418
Epoch 90/100
100/3021 [..............................] - ETA: 0s - loss: 0.0634 - mse: 0.0634
2700/3021 [=========================>....] - ETA: 0s - loss: 0.0709 - mse: 0.0709
3021/3021 [==============================] - 0s 151us/sample - loss: 0.0695 - mse: 0.0695 - val_loss: 0.0475 - val_mse: 0.0475
Epoch 91/100
100/3021 [..............................] - ETA: 0s - loss: 0.0862 - mse: 0.0862
2600/3021 [========================>.....] - ETA: 0s - loss: 0.0679 - mse: 0.0679
3021/3021 [==============================] - 0s 151us/sample - loss: 0.0680 - mse: 0.0680 - val_loss: 0.0380 - val_mse: 0.0380
Epoch 92/100
100/3021 [..............................] - ETA: 0s - loss: 0.0739 - mse: 0.0739
900/3021 [=======>......................] - ETA: 0s - loss: 0.0698 - mse: 0.0698
2100/3021 [===================>..........] - ETA: 0s - loss: 0.0675 - mse: 0.0675
3021/3021 [==============================] - 1s 208us/sample - loss: 0.0664 - mse: 0.0664 - val_loss: 0.0407 - val_mse: 0.0407
Epoch 93/100
100/3021 [..............................] - ETA: 0s - loss: 0.0585 - mse: 0.0585
2400/3021 [======================>.......] - ETA: 0s - loss: 0.0703 - mse: 0.0703
3021/3021 [==============================] - 0s 160us/sample - loss: 0.0682 - mse: 0.0682 - val_loss: 0.0356 - val_mse: 0.0356
Epoch 94/100
100/3021 [..............................] - ETA: 0s - loss: 0.0552 - mse: 0.0552
2000/3021 [==================>...........] - ETA: 0s - loss: 0.0638 - mse: 0.0638
3021/3021 [==============================] - 1s 184us/sample - loss: 0.0682 - mse: 0.0682 - val_loss: 0.0399 - val_mse: 0.0399
Epoch 95/100
100/3021 [..............................] - ETA: 0s - loss: 0.0717 - mse: 0.0717
1700/3021 [===============>..............] - ETA: 0s - loss: 0.0696 - mse: 0.0696
3021/3021 [==============================] - 1s 179us/sample - loss: 0.0676 - mse: 0.0676 - val_loss: 0.0372 - val_mse: 0.0372
Epoch 96/100
100/3021 [..............................] - ETA: 0s - loss: 0.0522 - mse: 0.0522
2200/3021 [====================>.........] - ETA: 0s - loss: 0.0679 - mse: 0.0679
3021/3021 [==============================] - 1s 171us/sample - loss: 0.0686 - mse: 0.0686 - val_loss: 0.0395 - val_mse: 0.0395
Epoch 97/100
100/3021 [..............................] - ETA: 0s - loss: 0.0643 - mse: 0.0643
1100/3021 [=========>....................] - ETA: 0s - loss: 0.0716 - mse: 0.0716
2600/3021 [========================>.....] - ETA: 0s - loss: 0.0705 - mse: 0.0705
3021/3021 [==============================] - 1s 221us/sample - loss: 0.0684 - mse: 0.0684 - val_loss: 0.0431 - val_mse: 0.0431
Epoch 98/100
100/3021 [..............................] - ETA: 0s - loss: 0.0597 - mse: 0.0597
2400/3021 [======================>.......] - ETA: 0s - loss: 0.0641 - mse: 0.0641
3021/3021 [==============================] - 0s 160us/sample - loss: 0.0637 - mse: 0.0637 - val_loss: 0.0359 - val_mse: 0.0359
Epoch 99/100
100/3021 [..............................] - ETA: 0s - loss: 0.0500 - mse: 0.0500
1700/3021 [===============>..............] - ETA: 0s - loss: 0.0632 - mse: 0.0632
3021/3021 [==============================] - 1s 177us/sample - loss: 0.0632 - mse: 0.0632 - val_loss: 0.0392 - val_mse: 0.0392
Epoch 100/100
100/3021 [..............................] - ETA: 0s - loss: 0.0729 - mse: 0.0729
2000/3021 [==================>...........] - ETA: 0s - loss: 0.0672 - mse: 0.0672
3021/3021 [==============================] - 1s 193us/sample - loss: 0.0643 - mse: 0.0643 - val_loss: 0.0474 - val_mse: 0.0474Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-05-04T01-08-34Z
Training run 35/46 (flags = list(392, 392, 1e-04, 200, 50, "tanh", "tanh", 0.05, 0.5))
Using run directory runs/2020-05-04T01-09-26Z
> FLAGS <- flags(
+ flag_numeric("nodes1", 128),
+ flag_numeric("nodes2", 128),
+ flag_numeric("batch_size", 100),
+ flag_string("activation1" .... [TRUNCATED]
> model = keras_model_sequential()
> model %>%
+ layer_dense(units=FLAGS$nodes1, activation=FLAGS$activation1, input_shape=dim(efw_train2)[2]) %>%
+ layer_dropout(FLAGS$dropout1) %> .... [TRUNCATED]
> model %>% compile(
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ loss = 'mse',
+ metrics = c('mse')
+ )
> model %>% fit(
+ as.matrix(efw_train2), train2Label,
+ epochs=FLAGS$epochs,
+ batch_size=FLAGS$batch_size,
+ validation_data=list(as.matrix( .... [TRUNCATED]
Train on 3021 samples, validate on 334 samples
Epoch 1/50
200/3021 [>.............................] - ETA: 3s - loss: 43.8080 - mse: 43.8080
2600/3021 [========================>.....] - ETA: 0s - loss: 42.9911 - mse: 42.9911
3021/3021 [==============================] - 1s 277us/sample - loss: 42.8300 - mse: 42.8300 - val_loss: 41.6730 - val_mse: 41.6730
Epoch 2/50
200/3021 [>.............................] - ETA: 0s - loss: 42.2748 - mse: 42.2748
2400/3021 [======================>.......] - ETA: 0s - loss: 41.2425 - mse: 41.2425
3021/3021 [==============================] - 0s 158us/sample - loss: 40.9665 - mse: 40.9665 - val_loss: 40.4235 - val_mse: 40.4235
Epoch 3/50
200/3021 [>.............................] - ETA: 0s - loss: 40.3871 - mse: 40.3871
2400/3021 [======================>.......] - ETA: 0s - loss: 39.7402 - mse: 39.7402
3021/3021 [==============================] - 1s 168us/sample - loss: 39.6240 - mse: 39.6240 - val_loss: 39.2571 - val_mse: 39.2571
Epoch 4/50
200/3021 [>.............................] - ETA: 0s - loss: 38.5491 - mse: 38.5491
2000/3021 [==================>...........] - ETA: 0s - loss: 38.5495 - mse: 38.5495
3021/3021 [==============================] - 0s 156us/sample - loss: 38.3704 - mse: 38.3704 - val_loss: 38.0929 - val_mse: 38.0929
Epoch 5/50
200/3021 [>.............................] - ETA: 0s - loss: 37.8948 - mse: 37.8948
2800/3021 [==========================>...] - ETA: 0s - loss: 37.2366 - mse: 37.2366
3021/3021 [==============================] - 1s 166us/sample - loss: 37.1605 - mse: 37.1605 - val_loss: 36.9589 - val_mse: 36.9589
Epoch 6/50
200/3021 [>.............................] - ETA: 0s - loss: 37.0317 - mse: 37.0317
2200/3021 [====================>.........] - ETA: 0s - loss: 36.1882 - mse: 36.1882
3021/3021 [==============================] - 0s 149us/sample - loss: 35.9730 - mse: 35.9730 - val_loss: 35.7836 - val_mse: 35.7836
Epoch 7/50
200/3021 [>.............................] - ETA: 0s - loss: 35.6946 - mse: 35.6946
2800/3021 [==========================>...] - ETA: 0s - loss: 34.7806 - mse: 34.7806
3021/3021 [==============================] - 0s 157us/sample - loss: 34.7345 - mse: 34.7345 - val_loss: 34.6176 - val_mse: 34.6176
Epoch 8/50
200/3021 [>.............................] - ETA: 0s - loss: 33.9520 - mse: 33.9520
2200/3021 [====================>.........] - ETA: 0s - loss: 33.6950 - mse: 33.6950
3021/3021 [==============================] - 0s 163us/sample - loss: 33.5439 - mse: 33.5439 - val_loss: 33.3526 - val_mse: 33.3526
Epoch 9/50
200/3021 [>.............................] - ETA: 0s - loss: 33.4389 - mse: 33.4389
2200/3021 [====================>.........] - ETA: 0s - loss: 32.4026 - mse: 32.4026
3021/3021 [==============================] - 1s 166us/sample - loss: 32.2213 - mse: 32.2213 - val_loss: 32.0889 - val_mse: 32.0889
Epoch 10/50
200/3021 [>.............................] - ETA: 0s - loss: 31.6325 - mse: 31.6325
2800/3021 [==========================>...] - ETA: 0s - loss: 30.9074 - mse: 30.9074
3021/3021 [==============================] - 0s 158us/sample - loss: 30.8569 - mse: 30.8569 - val_loss: 30.7990 - val_mse: 30.7990
Epoch 11/50
200/3021 [>.............................] - ETA: 0s - loss: 29.6904 - mse: 29.6904
2000/3021 [==================>...........] - ETA: 0s - loss: 29.7432 - mse: 29.7432
3021/3021 [==============================] - 0s 157us/sample - loss: 29.5647 - mse: 29.5647 - val_loss: 29.4663 - val_mse: 29.4663
Epoch 12/50
200/3021 [>.............................] - ETA: 0s - loss: 29.3814 - mse: 29.3814
2600/3021 [========================>.....] - ETA: 0s - loss: 28.2735 - mse: 28.2735
3021/3021 [==============================] - 0s 152us/sample - loss: 28.1516 - mse: 28.1516 - val_loss: 28.0778 - val_mse: 28.0778
Epoch 13/50
200/3021 [>.............................] - ETA: 0s - loss: 27.2500 - mse: 27.2500
2400/3021 [======================>.......] - ETA: 0s - loss: 26.9078 - mse: 26.9078
3021/3021 [==============================] - 0s 161us/sample - loss: 26.7798 - mse: 26.7798 - val_loss: 26.7057 - val_mse: 26.7057
Epoch 14/50
200/3021 [>.............................] - ETA: 0s - loss: 26.2184 - mse: 26.2184
2400/3021 [======================>.......] - ETA: 0s - loss: 25.5747 - mse: 25.5747
3021/3021 [==============================] - 0s 152us/sample - loss: 25.3558 - mse: 25.3558 - val_loss: 25.2994 - val_mse: 25.2994
Epoch 15/50
200/3021 [>.............................] - ETA: 0s - loss: 24.2736 - mse: 24.2736
2600/3021 [========================>.....] - ETA: 0s - loss: 24.0615 - mse: 24.0615
3021/3021 [==============================] - 0s 150us/sample - loss: 23.9407 - mse: 23.9407 - val_loss: 23.8027 - val_mse: 23.8027
Epoch 16/50
200/3021 [>.............................] - ETA: 0s - loss: 23.1222 - mse: 23.1222
2600/3021 [========================>.....] - ETA: 0s - loss: 22.5779 - mse: 22.5779
3021/3021 [==============================] - 0s 164us/sample - loss: 22.4540 - mse: 22.4540 - val_loss: 22.3726 - val_mse: 22.3726
Epoch 17/50
200/3021 [>.............................] - ETA: 0s - loss: 21.5179 - mse: 21.5179
2000/3021 [==================>...........] - ETA: 0s - loss: 21.2379 - mse: 21.2379
3021/3021 [==============================] - 0s 155us/sample - loss: 21.0090 - mse: 21.0090 - val_loss: 20.9390 - val_mse: 20.9390
Epoch 18/50
200/3021 [>.............................] - ETA: 0s - loss: 19.8867 - mse: 19.8867
2600/3021 [========================>.....] - ETA: 0s - loss: 19.6012 - mse: 19.6012
3021/3021 [==============================] - 0s 160us/sample - loss: 19.5152 - mse: 19.5152 - val_loss: 19.4466 - val_mse: 19.4466
Epoch 19/50
200/3021 [>.............................] - ETA: 0s - loss: 18.2961 - mse: 18.2961
2400/3021 [======================>.......] - ETA: 0s - loss: 18.2424 - mse: 18.2424
3021/3021 [==============================] - 0s 155us/sample - loss: 18.1202 - mse: 18.1202 - val_loss: 18.0072 - val_mse: 18.0072
Epoch 20/50
200/3021 [>.............................] - ETA: 0s - loss: 17.5400 - mse: 17.5400
2600/3021 [========================>.....] - ETA: 0s - loss: 16.7913 - mse: 16.7913
3021/3021 [==============================] - 0s 158us/sample - loss: 16.7287 - mse: 16.7287 - val_loss: 16.6170 - val_mse: 16.6170
Epoch 21/50
200/3021 [>.............................] - ETA: 0s - loss: 16.3312 - mse: 16.3312
2600/3021 [========================>.....] - ETA: 0s - loss: 15.4823 - mse: 15.4823
3021/3021 [==============================] - 0s 153us/sample - loss: 15.4051 - mse: 15.4051 - val_loss: 15.2500 - val_mse: 15.2500
Epoch 22/50
200/3021 [>.............................] - ETA: 0s - loss: 14.6000 - mse: 14.6000
2000/3021 [==================>...........] - ETA: 0s - loss: 14.2270 - mse: 14.2270
3021/3021 [==============================] - 1s 179us/sample - loss: 14.0331 - mse: 14.0331 - val_loss: 13.9902 - val_mse: 13.9902
Epoch 23/50
200/3021 [>.............................] - ETA: 0s - loss: 13.2872 - mse: 13.2872
2000/3021 [==================>...........] - ETA: 0s - loss: 13.0333 - mse: 13.0333
3021/3021 [==============================] - 0s 158us/sample - loss: 12.7598 - mse: 12.7598 - val_loss: 12.7274 - val_mse: 12.7274
Epoch 24/50
200/3021 [>.............................] - ETA: 0s - loss: 11.9690 - mse: 11.9690
2800/3021 [==========================>...] - ETA: 0s - loss: 11.5851 - mse: 11.5851
3021/3021 [==============================] - 0s 155us/sample - loss: 11.5592 - mse: 11.5592 - val_loss: 11.4841 - val_mse: 11.4841
Epoch 25/50
200/3021 [>.............................] - ETA: 0s - loss: 10.7212 - mse: 10.7212
1800/3021 [================>.............] - ETA: 0s - loss: 10.5444 - mse: 10.5444
3021/3021 [==============================] - 0s 163us/sample - loss: 10.3924 - mse: 10.3924 - val_loss: 10.3418 - val_mse: 10.3418
Epoch 26/50
200/3021 [>.............................] - ETA: 0s - loss: 9.4655 - mse: 9.4655
2600/3021 [========================>.....] - ETA: 0s - loss: 9.3699 - mse: 9.3699
3021/3021 [==============================] - 0s 159us/sample - loss: 9.2983 - mse: 9.2983 - val_loss: 9.2494 - val_mse: 9.2494
Epoch 27/50
200/3021 [>.............................] - ETA: 0s - loss: 9.0260 - mse: 9.0260
2800/3021 [==========================>...] - ETA: 0s - loss: 8.3123 - mse: 8.3123
3021/3021 [==============================] - 0s 151us/sample - loss: 8.2649 - mse: 8.2649 - val_loss: 8.2388 - val_mse: 8.2388
Epoch 28/50
200/3021 [>.............................] - ETA: 0s - loss: 7.7312 - mse: 7.7312
2600/3021 [========================>.....] - ETA: 0s - loss: 7.3717 - mse: 7.3717
3021/3021 [==============================] - 0s 159us/sample - loss: 7.3030 - mse: 7.3030 - val_loss: 7.3086 - val_mse: 7.3086
Epoch 29/50
200/3021 [>.............................] - ETA: 0s - loss: 6.6521 - mse: 6.6521
2600/3021 [========================>.....] - ETA: 0s - loss: 6.4453 - mse: 6.4453
3021/3021 [==============================] - 0s 155us/sample - loss: 6.4271 - mse: 6.4271 - val_loss: 6.3870 - val_mse: 6.3870
Epoch 30/50
200/3021 [>.............................] - ETA: 0s - loss: 6.1313 - mse: 6.1313
3000/3021 [============================>.] - ETA: 0s - loss: 5.5846 - mse: 5.5846
3021/3021 [==============================] - 0s 156us/sample - loss: 5.5819 - mse: 5.5819 - val_loss: 5.5966 - val_mse: 5.5966
Epoch 31/50
200/3021 [>.............................] - ETA: 0s - loss: 4.8943 - mse: 4.8943
3000/3021 [============================>.] - ETA: 0s - loss: 4.8864 - mse: 4.8864
3021/3021 [==============================] - 0s 153us/sample - loss: 4.8815 - mse: 4.8815 - val_loss: 4.8581 - val_mse: 4.8581
Epoch 32/50
200/3021 [>.............................] - ETA: 0s - loss: 4.6898 - mse: 4.6898
2200/3021 [====================>.........] - ETA: 0s - loss: 4.2606 - mse: 4.2606
3021/3021 [==============================] - 1s 175us/sample - loss: 4.1997 - mse: 4.1997 - val_loss: 4.2039 - val_mse: 4.2039
Epoch 33/50
200/3021 [>.............................] - ETA: 0s - loss: 3.7211 - mse: 3.7211
2200/3021 [====================>.........] - ETA: 0s - loss: 3.6585 - mse: 3.6585
3021/3021 [==============================] - 0s 153us/sample - loss: 3.5922 - mse: 3.5922 - val_loss: 3.6264 - val_mse: 3.6264
Epoch 34/50
200/3021 [>.............................] - ETA: 0s - loss: 3.5159 - mse: 3.5159
2600/3021 [========================>.....] - ETA: 0s - loss: 3.0888 - mse: 3.0889
3021/3021 [==============================] - 0s 154us/sample - loss: 3.0656 - mse: 3.0656 - val_loss: 3.0947 - val_mse: 3.0947
Epoch 35/50
200/3021 [>.............................] - ETA: 0s - loss: 2.6920 - mse: 2.6920
2600/3021 [========================>.....] - ETA: 0s - loss: 2.6003 - mse: 2.6003
3021/3021 [==============================] - 0s 162us/sample - loss: 2.5866 - mse: 2.5866 - val_loss: 2.6332 - val_mse: 2.6332
Epoch 36/50
200/3021 [>.............................] - ETA: 0s - loss: 2.4233 - mse: 2.4233
2400/3021 [======================>.......] - ETA: 0s - loss: 2.2277 - mse: 2.2277
3021/3021 [==============================] - 0s 164us/sample - loss: 2.1816 - mse: 2.1816 - val_loss: 2.2200 - val_mse: 2.2200
Epoch 37/50
200/3021 [>.............................] - ETA: 0s - loss: 1.9848 - mse: 1.9848
1800/3021 [================>.............] - ETA: 0s - loss: 1.9073 - mse: 1.9073
3021/3021 [==============================] - 0s 161us/sample - loss: 1.8472 - mse: 1.8472 - val_loss: 1.8569 - val_mse: 1.8569
Epoch 38/50
200/3021 [>.............................] - ETA: 0s - loss: 1.7214 - mse: 1.7214
2200/3021 [====================>.........] - ETA: 0s - loss: 1.5777 - mse: 1.5777
3021/3021 [==============================] - 0s 161us/sample - loss: 1.5471 - mse: 1.5471 - val_loss: 1.5485 - val_mse: 1.5485
Epoch 39/50
200/3021 [>.............................] - ETA: 0s - loss: 1.3789 - mse: 1.3789
2400/3021 [======================>.......] - ETA: 0s - loss: 1.3068 - mse: 1.3068
3021/3021 [==============================] - 0s 158us/sample - loss: 1.2749 - mse: 1.2749 - val_loss: 1.2884 - val_mse: 1.2884
Epoch 40/50
200/3021 [>.............................] - ETA: 0s - loss: 1.1013 - mse: 1.1013
2200/3021 [====================>.........] - ETA: 0s - loss: 1.0990 - mse: 1.0990
3021/3021 [==============================] - 0s 155us/sample - loss: 1.0629 - mse: 1.0629 - val_loss: 1.0722 - val_mse: 1.0722
Epoch 41/50
200/3021 [>.............................] - ETA: 0s - loss: 1.0005 - mse: 1.0005
2800/3021 [==========================>...] - ETA: 0s - loss: 0.8628 - mse: 0.8628
3021/3021 [==============================] - 0s 154us/sample - loss: 0.8667 - mse: 0.8667 - val_loss: 0.8921 - val_mse: 0.8921
Epoch 42/50
200/3021 [>.............................] - ETA: 0s - loss: 0.8134 - mse: 0.8134
2600/3021 [========================>.....] - ETA: 0s - loss: 0.7338 - mse: 0.7338
3021/3021 [==============================] - 0s 152us/sample - loss: 0.7241 - mse: 0.7241 - val_loss: 0.7401 - val_mse: 0.7401
Epoch 43/50
200/3021 [>.............................] - ETA: 0s - loss: 0.6537 - mse: 0.6537
2600/3021 [========================>.....] - ETA: 0s - loss: 0.6158 - mse: 0.6158
3021/3021 [==============================] - 0s 164us/sample - loss: 0.5988 - mse: 0.5988 - val_loss: 0.6133 - val_mse: 0.6133
Epoch 44/50
200/3021 [>.............................] - ETA: 0s - loss: 0.4671 - mse: 0.4671
2200/3021 [====================>.........] - ETA: 0s - loss: 0.4994 - mse: 0.4994
3021/3021 [==============================] - 0s 155us/sample - loss: 0.4880 - mse: 0.4880 - val_loss: 0.5087 - val_mse: 0.5087
Epoch 45/50
200/3021 [>.............................] - ETA: 0s - loss: 0.4643 - mse: 0.4643
2800/3021 [==========================>...] - ETA: 0s - loss: 0.4123 - mse: 0.4123
3021/3021 [==============================] - 0s 163us/sample - loss: 0.4088 - mse: 0.4088 - val_loss: 0.4275 - val_mse: 0.4275
Epoch 46/50
200/3021 [>.............................] - ETA: 0s - loss: 0.4265 - mse: 0.4265
2000/3021 [==================>...........] - ETA: 0s - loss: 0.3663 - mse: 0.3663
3021/3021 [==============================] - 0s 153us/sample - loss: 0.3483 - mse: 0.3483 - val_loss: 0.3612 - val_mse: 0.3612
Epoch 47/50
200/3021 [>.............................] - ETA: 0s - loss: 0.3149 - mse: 0.3149
2800/3021 [==========================>...] - ETA: 0s - loss: 0.3011 - mse: 0.3011
3021/3021 [==============================] - 0s 150us/sample - loss: 0.2968 - mse: 0.2968 - val_loss: 0.3009 - val_mse: 0.3009
Epoch 48/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2584 - mse: 0.2584
2800/3021 [==========================>...] - ETA: 0s - loss: 0.2562 - mse: 0.2562
3021/3021 [==============================] - 0s 147us/sample - loss: 0.2550 - mse: 0.2550 - val_loss: 0.2574 - val_mse: 0.2574
Epoch 49/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2256 - mse: 0.2256
2600/3021 [========================>.....] - ETA: 0s - loss: 0.2234 - mse: 0.2234
3021/3021 [==============================] - 1s 170us/sample - loss: 0.2160 - mse: 0.2160 - val_loss: 0.2207 - val_mse: 0.2207
Epoch 50/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2227 - mse: 0.2227
2600/3021 [========================>.....] - ETA: 0s - loss: 0.2026 - mse: 0.2026
3021/3021 [==============================] - 0s 146us/sample - loss: 0.1993 - mse: 0.1993 - val_loss: 0.1933 - val_mse: 0.1933Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-05-04T01-09-26Z
Training run 36/46 (flags = list(392, 64, 0.05, 200, 100, "relu", "tanh", 0.2, 0.05))
Using run directory runs/2020-05-04T01-09-55Z
> FLAGS <- flags(
+ flag_numeric("nodes1", 128),
+ flag_numeric("nodes2", 128),
+ flag_numeric("batch_size", 100),
+ flag_string("activation1" .... [TRUNCATED]
> model = keras_model_sequential()
> model %>%
+ layer_dense(units=FLAGS$nodes1, activation=FLAGS$activation1, input_shape=dim(efw_train2)[2]) %>%
+ layer_dropout(FLAGS$dropout1) %> .... [TRUNCATED]
> model %>% compile(
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ loss = 'mse',
+ metrics = c('mse')
+ )
> model %>% fit(
+ as.matrix(efw_train2), train2Label,
+ epochs=FLAGS$epochs,
+ batch_size=FLAGS$batch_size,
+ validation_data=list(as.matrix( .... [TRUNCATED]
Train on 3021 samples, validate on 334 samples
Epoch 1/100
200/3021 [>.............................] - ETA: 4s - loss: 39.3726 - mse: 39.3726
2400/3021 [======================>.......] - ETA: 0s - loss: 15.7914 - mse: 15.7914
3021/3021 [==============================] - 1s 268us/sample - loss: 13.7760 - mse: 13.7760 - val_loss: 6.4070 - val_mse: 6.4070
Epoch 2/100
200/3021 [>.............................] - ETA: 0s - loss: 6.7005 - mse: 6.7005
2400/3021 [======================>.......] - ETA: 0s - loss: 3.5800 - mse: 3.5800
3021/3021 [==============================] - 0s 162us/sample - loss: 3.1756 - mse: 3.1756 - val_loss: 2.2383 - val_mse: 2.2383
Epoch 3/100
200/3021 [>.............................] - ETA: 0s - loss: 1.6532 - mse: 1.6532
2400/3021 [======================>.......] - ETA: 0s - loss: 1.2159 - mse: 1.2159
3021/3021 [==============================] - 1s 171us/sample - loss: 1.1390 - mse: 1.1390 - val_loss: 1.2888 - val_mse: 1.2888
Epoch 4/100
200/3021 [>.............................] - ETA: 0s - loss: 1.2773 - mse: 1.2773
2600/3021 [========================>.....] - ETA: 0s - loss: 0.9531 - mse: 0.9531
3021/3021 [==============================] - 0s 165us/sample - loss: 0.9041 - mse: 0.9041 - val_loss: 0.9996 - val_mse: 0.9996
Epoch 5/100
200/3021 [>.............................] - ETA: 0s - loss: 0.9571 - mse: 0.9571
2400/3021 [======================>.......] - ETA: 0s - loss: 0.6999 - mse: 0.6999
3021/3021 [==============================] - 1s 170us/sample - loss: 0.6908 - mse: 0.6908 - val_loss: 0.3813 - val_mse: 0.3813
Epoch 6/100
200/3021 [>.............................] - ETA: 0s - loss: 0.4617 - mse: 0.4617
2600/3021 [========================>.....] - ETA: 0s - loss: 0.4143 - mse: 0.4143
3021/3021 [==============================] - 0s 155us/sample - loss: 0.4093 - mse: 0.4093 - val_loss: 0.2146 - val_mse: 0.2146
Epoch 7/100
200/3021 [>.............................] - ETA: 0s - loss: 0.2754 - mse: 0.2754
2000/3021 [==================>...........] - ETA: 0s - loss: 0.2982 - mse: 0.2982
3021/3021 [==============================] - 1s 171us/sample - loss: 0.3100 - mse: 0.3100 - val_loss: 0.3281 - val_mse: 0.3281
Epoch 8/100
200/3021 [>.............................] - ETA: 0s - loss: 0.4225 - mse: 0.4225
2600/3021 [========================>.....] - ETA: 0s - loss: 0.3117 - mse: 0.3117
3021/3021 [==============================] - 0s 155us/sample - loss: 0.3049 - mse: 0.3049 - val_loss: 0.2596 - val_mse: 0.2596
Epoch 9/100
200/3021 [>.............................] - ETA: 0s - loss: 0.3003 - mse: 0.3003
2400/3021 [======================>.......] - ETA: 0s - loss: 0.3238 - mse: 0.3238
3021/3021 [==============================] - 0s 158us/sample - loss: 0.3145 - mse: 0.3145 - val_loss: 0.1429 - val_mse: 0.1429
Epoch 10/100
200/3021 [>.............................] - ETA: 0s - loss: 0.2334 - mse: 0.2334
2400/3021 [======================>.......] - ETA: 0s - loss: 0.2290 - mse: 0.2290
3021/3021 [==============================] - 0s 165us/sample - loss: 0.2264 - mse: 0.2264 - val_loss: 0.1185 - val_mse: 0.1185
Epoch 11/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1863 - mse: 0.1863
2200/3021 [====================>.........] - ETA: 0s - loss: 0.2124 - mse: 0.2124
3021/3021 [==============================] - 1s 172us/sample - loss: 0.2101 - mse: 0.2101 - val_loss: 0.1112 - val_mse: 0.1112
Epoch 12/100
200/3021 [>.............................] - ETA: 0s - loss: 0.2110 - mse: 0.2110
2600/3021 [========================>.....] - ETA: 0s - loss: 0.2235 - mse: 0.2235
3021/3021 [==============================] - 0s 157us/sample - loss: 0.2235 - mse: 0.2235 - val_loss: 0.2960 - val_mse: 0.2960
Epoch 13/100
200/3021 [>.............................] - ETA: 0s - loss: 0.3648 - mse: 0.3648
2600/3021 [========================>.....] - ETA: 0s - loss: 0.3136 - mse: 0.3136
3021/3021 [==============================] - 0s 163us/sample - loss: 0.3074 - mse: 0.3074 - val_loss: 0.3910 - val_mse: 0.3910
Epoch 14/100
200/3021 [>.............................] - ETA: 0s - loss: 0.4492 - mse: 0.4492
2000/3021 [==================>...........] - ETA: 0s - loss: 0.3877 - mse: 0.3877
3021/3021 [==============================] - 0s 162us/sample - loss: 0.3536 - mse: 0.3536 - val_loss: 0.1422 - val_mse: 0.1422
Epoch 15/100
200/3021 [>.............................] - ETA: 0s - loss: 0.2591 - mse: 0.2591
2600/3021 [========================>.....] - ETA: 0s - loss: 0.2030 - mse: 0.2030
3021/3021 [==============================] - 0s 155us/sample - loss: 0.2004 - mse: 0.2004 - val_loss: 0.1196 - val_mse: 0.1196
Epoch 16/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1830 - mse: 0.1830
2400/3021 [======================>.......] - ETA: 0s - loss: 0.2039 - mse: 0.2039
3021/3021 [==============================] - 1s 176us/sample - loss: 0.2017 - mse: 0.2017 - val_loss: 0.1472 - val_mse: 0.1472
Epoch 17/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1973 - mse: 0.1973
2400/3021 [======================>.......] - ETA: 0s - loss: 0.1986 - mse: 0.1986
3021/3021 [==============================] - 1s 174us/sample - loss: 0.1957 - mse: 0.1957 - val_loss: 0.2364 - val_mse: 0.2364
Epoch 18/100
200/3021 [>.............................] - ETA: 0s - loss: 0.2682 - mse: 0.2682
2600/3021 [========================>.....] - ETA: 0s - loss: 0.2396 - mse: 0.2396
3021/3021 [==============================] - 0s 159us/sample - loss: 0.2345 - mse: 0.2345 - val_loss: 0.1768 - val_mse: 0.1768
Epoch 19/100
200/3021 [>.............................] - ETA: 0s - loss: 0.2558 - mse: 0.2558
2200/3021 [====================>.........] - ETA: 0s - loss: 0.2358 - mse: 0.2358
3021/3021 [==============================] - 1s 172us/sample - loss: 0.2350 - mse: 0.2350 - val_loss: 0.1856 - val_mse: 0.1856
Epoch 20/100
200/3021 [>.............................] - ETA: 0s - loss: 0.2494 - mse: 0.2494
2200/3021 [====================>.........] - ETA: 0s - loss: 0.2206 - mse: 0.2206
3021/3021 [==============================] - 1s 168us/sample - loss: 0.2090 - mse: 0.2090 - val_loss: 0.1957 - val_mse: 0.1957
Epoch 21/100
200/3021 [>.............................] - ETA: 0s - loss: 0.2061 - mse: 0.2061
2200/3021 [====================>.........] - ETA: 0s - loss: 0.2351 - mse: 0.2351
3021/3021 [==============================] - 1s 173us/sample - loss: 0.2210 - mse: 0.2210 - val_loss: 0.1751 - val_mse: 0.1751
Epoch 22/100
200/3021 [>.............................] - ETA: 0s - loss: 0.2285 - mse: 0.2285
2600/3021 [========================>.....] - ETA: 0s - loss: 0.1821 - mse: 0.1821
3021/3021 [==============================] - 0s 160us/sample - loss: 0.1838 - mse: 0.1838 - val_loss: 0.1125 - val_mse: 0.1125
Epoch 23/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1617 - mse: 0.1617
2200/3021 [====================>.........] - ETA: 0s - loss: 0.1957 - mse: 0.1957
3021/3021 [==============================] - 1s 167us/sample - loss: 0.1909 - mse: 0.1909 - val_loss: 0.1258 - val_mse: 0.1258
Epoch 24/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1742 - mse: 0.1742
1800/3021 [================>.............] - ETA: 0s - loss: 0.1701 - mse: 0.1701
3021/3021 [==============================] - 0s 164us/sample - loss: 0.1713 - mse: 0.1713 - val_loss: 0.1244 - val_mse: 0.1244
Epoch 25/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1524 - mse: 0.1524
2600/3021 [========================>.....] - ETA: 0s - loss: 0.1725 - mse: 0.1725
3021/3021 [==============================] - 0s 150us/sample - loss: 0.1712 - mse: 0.1712 - val_loss: 0.0995 - val_mse: 0.0995
Epoch 26/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1623 - mse: 0.1623
2600/3021 [========================>.....] - ETA: 0s - loss: 0.1548 - mse: 0.1548
3021/3021 [==============================] - 1s 183us/sample - loss: 0.1517 - mse: 0.1517 - val_loss: 0.1359 - val_mse: 0.1359
Epoch 27/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1847 - mse: 0.1847
1800/3021 [================>.............] - ETA: 0s - loss: 0.1332 - mse: 0.1332
3000/3021 [============================>.] - ETA: 0s - loss: 0.1366 - mse: 0.1366
3021/3021 [==============================] - 1s 194us/sample - loss: 0.1368 - mse: 0.1368 - val_loss: 0.0807 - val_mse: 0.0807
Epoch 28/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1112 - mse: 0.1112
2600/3021 [========================>.....] - ETA: 0s - loss: 0.1475 - mse: 0.1475
3021/3021 [==============================] - 0s 161us/sample - loss: 0.1477 - mse: 0.1477 - val_loss: 0.1048 - val_mse: 0.1048
Epoch 29/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1184 - mse: 0.1184
2400/3021 [======================>.......] - ETA: 0s - loss: 0.2026 - mse: 0.2026
3021/3021 [==============================] - 0s 164us/sample - loss: 0.1928 - mse: 0.1928 - val_loss: 0.0966 - val_mse: 0.0966
Epoch 30/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1067 - mse: 0.1067
2400/3021 [======================>.......] - ETA: 0s - loss: 0.1469 - mse: 0.1469
3021/3021 [==============================] - 0s 161us/sample - loss: 0.1440 - mse: 0.1440 - val_loss: 0.0802 - val_mse: 0.0802
Epoch 31/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1095 - mse: 0.1095
2600/3021 [========================>.....] - ETA: 0s - loss: 0.1661 - mse: 0.1661
3021/3021 [==============================] - 0s 155us/sample - loss: 0.1697 - mse: 0.1697 - val_loss: 0.2015 - val_mse: 0.2015
Epoch 32/100
200/3021 [>.............................] - ETA: 0s - loss: 0.2626 - mse: 0.2626
2000/3021 [==================>...........] - ETA: 0s - loss: 0.2004 - mse: 0.2004
3021/3021 [==============================] - 1s 191us/sample - loss: 0.1918 - mse: 0.1918 - val_loss: 0.1278 - val_mse: 0.1278
Epoch 33/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1525 - mse: 0.1525
1800/3021 [================>.............] - ETA: 0s - loss: 0.2365 - mse: 0.2365
3021/3021 [==============================] - 1s 194us/sample - loss: 0.2165 - mse: 0.2165 - val_loss: 0.2287 - val_mse: 0.2287
Epoch 34/100
200/3021 [>.............................] - ETA: 0s - loss: 0.2050 - mse: 0.2050
2000/3021 [==================>...........] - ETA: 0s - loss: 0.2002 - mse: 0.2002
3021/3021 [==============================] - 1s 166us/sample - loss: 0.1770 - mse: 0.1770 - val_loss: 0.1213 - val_mse: 0.1213
Epoch 35/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1622 - mse: 0.1622
2600/3021 [========================>.....] - ETA: 0s - loss: 0.1686 - mse: 0.1686
3021/3021 [==============================] - 1s 167us/sample - loss: 0.1653 - mse: 0.1653 - val_loss: 0.1535 - val_mse: 0.1535
Epoch 36/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1949 - mse: 0.1949
2600/3021 [========================>.....] - ETA: 0s - loss: 0.1488 - mse: 0.1488
3021/3021 [==============================] - 0s 153us/sample - loss: 0.1522 - mse: 0.1522 - val_loss: 0.0980 - val_mse: 0.0980
Epoch 37/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1229 - mse: 0.1229
2600/3021 [========================>.....] - ETA: 0s - loss: 0.1566 - mse: 0.1566
3021/3021 [==============================] - 0s 165us/sample - loss: 0.1555 - mse: 0.1555 - val_loss: 0.1725 - val_mse: 0.1725
Epoch 38/100
200/3021 [>.............................] - ETA: 0s - loss: 0.2002 - mse: 0.2002
2200/3021 [====================>.........] - ETA: 0s - loss: 0.1730 - mse: 0.1730
3021/3021 [==============================] - 1s 168us/sample - loss: 0.1671 - mse: 0.1671 - val_loss: 0.1396 - val_mse: 0.1396
Epoch 39/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1276 - mse: 0.1276
2200/3021 [====================>.........] - ETA: 0s - loss: 0.1441 - mse: 0.1441
3021/3021 [==============================] - 1s 169us/sample - loss: 0.1468 - mse: 0.1468 - val_loss: 0.2878 - val_mse: 0.2878
Epoch 40/100
200/3021 [>.............................] - ETA: 0s - loss: 0.3223 - mse: 0.3223
2400/3021 [======================>.......] - ETA: 0s - loss: 0.2844 - mse: 0.2844
3021/3021 [==============================] - 0s 155us/sample - loss: 0.2743 - mse: 0.2743 - val_loss: 0.1917 - val_mse: 0.1917
Epoch 41/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1672 - mse: 0.1672
2600/3021 [========================>.....] - ETA: 0s - loss: 0.1860 - mse: 0.1860
3021/3021 [==============================] - 0s 160us/sample - loss: 0.1841 - mse: 0.1841 - val_loss: 0.3699 - val_mse: 0.3699
Epoch 42/100
200/3021 [>.............................] - ETA: 0s - loss: 0.4284 - mse: 0.4284
2800/3021 [==========================>...] - ETA: 0s - loss: 0.2965 - mse: 0.2965
3021/3021 [==============================] - 0s 161us/sample - loss: 0.2873 - mse: 0.2873 - val_loss: 0.1973 - val_mse: 0.1973
Epoch 43/100
200/3021 [>.............................] - ETA: 0s - loss: 0.2649 - mse: 0.2649
2600/3021 [========================>.....] - ETA: 0s - loss: 0.2599 - mse: 0.2599
3021/3021 [==============================] - 0s 154us/sample - loss: 0.2542 - mse: 0.2542 - val_loss: 0.1634 - val_mse: 0.1634
Epoch 44/100
200/3021 [>.............................] - ETA: 0s - loss: 0.2002 - mse: 0.2002
2000/3021 [==================>...........] - ETA: 0s - loss: 0.2150 - mse: 0.2150
3021/3021 [==============================] - 1s 181us/sample - loss: 0.1950 - mse: 0.1950 - val_loss: 0.1329 - val_mse: 0.1329
Epoch 45/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1612 - mse: 0.1612
2000/3021 [==================>...........] - ETA: 0s - loss: 0.1936 - mse: 0.1936
3021/3021 [==============================] - 1s 178us/sample - loss: 0.1972 - mse: 0.1972 - val_loss: 0.1962 - val_mse: 0.1962
Epoch 46/100
200/3021 [>.............................] - ETA: 0s - loss: 0.3259 - mse: 0.3259
2600/3021 [========================>.....] - ETA: 0s - loss: 0.1940 - mse: 0.1940
3021/3021 [==============================] - 0s 163us/sample - loss: 0.1874 - mse: 0.1874 - val_loss: 0.0936 - val_mse: 0.0936
Epoch 47/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0903 - mse: 0.0903
2600/3021 [========================>.....] - ETA: 0s - loss: 0.1648 - mse: 0.1648
3021/3021 [==============================] - 0s 159us/sample - loss: 0.1572 - mse: 0.1572 - val_loss: 0.1980 - val_mse: 0.1980
Epoch 48/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1882 - mse: 0.1882
2400/3021 [======================>.......] - ETA: 0s - loss: 0.1556 - mse: 0.1556
3021/3021 [==============================] - 0s 157us/sample - loss: 0.1486 - mse: 0.1486 - val_loss: 0.0796 - val_mse: 0.0796
Epoch 49/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0970 - mse: 0.0970
2200/3021 [====================>.........] - ETA: 0s - loss: 0.1273 - mse: 0.1273
3021/3021 [==============================] - 1s 170us/sample - loss: 0.1204 - mse: 0.1204 - val_loss: 0.2845 - val_mse: 0.2845
Epoch 50/100
200/3021 [>.............................] - ETA: 0s - loss: 0.2822 - mse: 0.2822
2800/3021 [==========================>...] - ETA: 0s - loss: 0.1662 - mse: 0.1662
3021/3021 [==============================] - 0s 152us/sample - loss: 0.1630 - mse: 0.1630 - val_loss: 0.1097 - val_mse: 0.1097
Epoch 51/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1240 - mse: 0.1240
2200/3021 [====================>.........] - ETA: 0s - loss: 0.1273 - mse: 0.1273
3021/3021 [==============================] - 1s 186us/sample - loss: 0.1270 - mse: 0.1270 - val_loss: 0.1062 - val_mse: 0.1062
Epoch 52/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1725 - mse: 0.1725
2400/3021 [======================>.......] - ETA: 0s - loss: 0.1507 - mse: 0.1507
3021/3021 [==============================] - 1s 175us/sample - loss: 0.1409 - mse: 0.1409 - val_loss: 0.0789 - val_mse: 0.0789
Epoch 53/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1049 - mse: 0.1049
2600/3021 [========================>.....] - ETA: 0s - loss: 0.1035 - mse: 0.1035
3021/3021 [==============================] - 0s 165us/sample - loss: 0.1027 - mse: 0.1027 - val_loss: 0.1152 - val_mse: 0.1152
Epoch 54/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1432 - mse: 0.1432
2800/3021 [==========================>...] - ETA: 0s - loss: 0.1114 - mse: 0.1114
3021/3021 [==============================] - 1s 170us/sample - loss: 0.1104 - mse: 0.1104 - val_loss: 0.0693 - val_mse: 0.0693
Epoch 55/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0855 - mse: 0.0855
2200/3021 [====================>.........] - ETA: 0s - loss: 0.0864 - mse: 0.0864
3021/3021 [==============================] - 1s 197us/sample - loss: 0.0833 - mse: 0.0833 - val_loss: 0.0851 - val_mse: 0.0851
Epoch 56/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1212 - mse: 0.1212
2400/3021 [======================>.......] - ETA: 0s - loss: 0.0880 - mse: 0.0880
3021/3021 [==============================] - 1s 180us/sample - loss: 0.0856 - mse: 0.0856 - val_loss: 0.0677 - val_mse: 0.0677
Epoch 57/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0833 - mse: 0.0833
2000/3021 [==================>...........] - ETA: 0s - loss: 0.0970 - mse: 0.0970
3021/3021 [==============================] - 1s 191us/sample - loss: 0.0885 - mse: 0.0885 - val_loss: 0.1220 - val_mse: 0.1220
Epoch 58/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1487 - mse: 0.1487
2400/3021 [======================>.......] - ETA: 0s - loss: 0.1495 - mse: 0.1495
3021/3021 [==============================] - 1s 169us/sample - loss: 0.1483 - mse: 0.1483 - val_loss: 0.3134 - val_mse: 0.3134
Epoch 59/100
200/3021 [>.............................] - ETA: 0s - loss: 0.3380 - mse: 0.3380
2400/3021 [======================>.......] - ETA: 0s - loss: 0.1986 - mse: 0.1986
3021/3021 [==============================] - 0s 154us/sample - loss: 0.2039 - mse: 0.2039 - val_loss: 0.0756 - val_mse: 0.0756
Epoch 60/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0907 - mse: 0.0907
2600/3021 [========================>.....] - ETA: 0s - loss: 0.1038 - mse: 0.1038
3021/3021 [==============================] - 0s 161us/sample - loss: 0.1036 - mse: 0.1036 - val_loss: 0.0864 - val_mse: 0.0864
Epoch 61/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0863 - mse: 0.0863
2400/3021 [======================>.......] - ETA: 0s - loss: 0.1018 - mse: 0.1018
3021/3021 [==============================] - 0s 160us/sample - loss: 0.1015 - mse: 0.1015 - val_loss: 0.3040 - val_mse: 0.3040
Epoch 62/100
200/3021 [>.............................] - ETA: 0s - loss: 0.2824 - mse: 0.2824
2200/3021 [====================>.........] - ETA: 0s - loss: 0.2030 - mse: 0.2030
3021/3021 [==============================] - 1s 172us/sample - loss: 0.1874 - mse: 0.1874 - val_loss: 0.1008 - val_mse: 0.1008
Epoch 63/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0941 - mse: 0.0941
2400/3021 [======================>.......] - ETA: 0s - loss: 0.1712 - mse: 0.1712
3021/3021 [==============================] - 1s 166us/sample - loss: 0.1599 - mse: 0.1599 - val_loss: 0.1378 - val_mse: 0.1378
Epoch 64/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1312 - mse: 0.1312
2600/3021 [========================>.....] - ETA: 0s - loss: 0.1429 - mse: 0.1429
3021/3021 [==============================] - 0s 163us/sample - loss: 0.1358 - mse: 0.1358 - val_loss: 0.1474 - val_mse: 0.1474
Epoch 65/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1798 - mse: 0.1798
1800/3021 [================>.............] - ETA: 0s - loss: 0.1237 - mse: 0.1237
3021/3021 [==============================] - 0s 160us/sample - loss: 0.1057 - mse: 0.1057 - val_loss: 0.0658 - val_mse: 0.0658
Epoch 66/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0871 - mse: 0.0871
2400/3021 [======================>.......] - ETA: 0s - loss: 0.0940 - mse: 0.0940
3021/3021 [==============================] - 0s 164us/sample - loss: 0.0944 - mse: 0.0944 - val_loss: 0.1071 - val_mse: 0.1071
Epoch 67/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1287 - mse: 0.1287
1800/3021 [================>.............] - ETA: 0s - loss: 0.0860 - mse: 0.0860
3021/3021 [==============================] - 0s 151us/sample - loss: 0.0771 - mse: 0.0771 - val_loss: 0.0523 - val_mse: 0.0523
Epoch 68/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0645 - mse: 0.0645
2600/3021 [========================>.....] - ETA: 0s - loss: 0.0735 - mse: 0.0735
3021/3021 [==============================] - 0s 152us/sample - loss: 0.0756 - mse: 0.0756 - val_loss: 0.0602 - val_mse: 0.0602
Epoch 69/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0751 - mse: 0.0751
2600/3021 [========================>.....] - ETA: 0s - loss: 0.0970 - mse: 0.0970
3021/3021 [==============================] - 0s 154us/sample - loss: 0.0948 - mse: 0.0948 - val_loss: 0.1046 - val_mse: 0.1046
Epoch 70/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1150 - mse: 0.1150
1600/3021 [==============>...............] - ETA: 0s - loss: 0.0931 - mse: 0.0931
3021/3021 [==============================] - 0s 152us/sample - loss: 0.0912 - mse: 0.0912 - val_loss: 0.1035 - val_mse: 0.1035
Epoch 71/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1138 - mse: 0.1138
2600/3021 [========================>.....] - ETA: 0s - loss: 0.0743 - mse: 0.0743
3021/3021 [==============================] - 0s 154us/sample - loss: 0.0742 - mse: 0.0742 - val_loss: 0.0639 - val_mse: 0.0639
Epoch 72/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0618 - mse: 0.0618
2600/3021 [========================>.....] - ETA: 0s - loss: 0.0869 - mse: 0.0869
3021/3021 [==============================] - 0s 157us/sample - loss: 0.0835 - mse: 0.0835 - val_loss: 0.0723 - val_mse: 0.0723
Epoch 73/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0614 - mse: 0.0614
2400/3021 [======================>.......] - ETA: 0s - loss: 0.0831 - mse: 0.0831
3021/3021 [==============================] - 0s 160us/sample - loss: 0.0770 - mse: 0.0770 - val_loss: 0.0526 - val_mse: 0.0526
Epoch 74/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0577 - mse: 0.0577
2600/3021 [========================>.....] - ETA: 0s - loss: 0.0643 - mse: 0.0643
3021/3021 [==============================] - 0s 151us/sample - loss: 0.0627 - mse: 0.0627 - val_loss: 0.0590 - val_mse: 0.0590
Epoch 75/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0754 - mse: 0.0754
2600/3021 [========================>.....] - ETA: 0s - loss: 0.0837 - mse: 0.0837
3021/3021 [==============================] - 1s 167us/sample - loss: 0.0803 - mse: 0.0803 - val_loss: 0.0555 - val_mse: 0.0555
Epoch 76/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0478 - mse: 0.0478
1800/3021 [================>.............] - ETA: 0s - loss: 0.0608 - mse: 0.0608
3021/3021 [==============================] - 0s 161us/sample - loss: 0.0560 - mse: 0.0560 - val_loss: 0.0759 - val_mse: 0.0759
Epoch 77/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0789 - mse: 0.0789
2800/3021 [==========================>...] - ETA: 0s - loss: 0.0921 - mse: 0.0921
3021/3021 [==============================] - 0s 152us/sample - loss: 0.0897 - mse: 0.0897 - val_loss: 0.0588 - val_mse: 0.0588
Epoch 78/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0624 - mse: 0.0624
1800/3021 [================>.............] - ETA: 0s - loss: 0.0754 - mse: 0.0754
3021/3021 [==============================] - 0s 158us/sample - loss: 0.0721 - mse: 0.0721 - val_loss: 0.0525 - val_mse: 0.0525
Epoch 79/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0590 - mse: 0.0590
2400/3021 [======================>.......] - ETA: 0s - loss: 0.0610 - mse: 0.0610
3021/3021 [==============================] - 0s 149us/sample - loss: 0.0613 - mse: 0.0613 - val_loss: 0.0527 - val_mse: 0.0527
Epoch 80/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0454 - mse: 0.0454
2800/3021 [==========================>...] - ETA: 0s - loss: 0.0598 - mse: 0.0598
3021/3021 [==============================] - 0s 150us/sample - loss: 0.0590 - mse: 0.0590 - val_loss: 0.0516 - val_mse: 0.0516
Epoch 81/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0515 - mse: 0.0515
2600/3021 [========================>.....] - ETA: 0s - loss: 0.0557 - mse: 0.0557
3021/3021 [==============================] - 0s 159us/sample - loss: 0.0539 - mse: 0.0539 - val_loss: 0.0445 - val_mse: 0.0445
Epoch 82/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0529 - mse: 0.0529
2400/3021 [======================>.......] - ETA: 0s - loss: 0.0521 - mse: 0.0521
3021/3021 [==============================] - 0s 160us/sample - loss: 0.0502 - mse: 0.0502 - val_loss: 0.0485 - val_mse: 0.0485
Epoch 83/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0413 - mse: 0.0413
2400/3021 [======================>.......] - ETA: 0s - loss: 0.0520 - mse: 0.0520
3021/3021 [==============================] - 0s 163us/sample - loss: 0.0542 - mse: 0.0542 - val_loss: 0.0885 - val_mse: 0.0885
Epoch 84/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0717 - mse: 0.0717
2000/3021 [==================>...........] - ETA: 0s - loss: 0.0561 - mse: 0.0561
3021/3021 [==============================] - 0s 159us/sample - loss: 0.0532 - mse: 0.0532 - val_loss: 0.0457 - val_mse: 0.0457
Epoch 85/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0477 - mse: 0.0477
2600/3021 [========================>.....] - ETA: 0s - loss: 0.0533 - mse: 0.0533
3021/3021 [==============================] - 0s 150us/sample - loss: 0.0520 - mse: 0.0520 - val_loss: 0.0746 - val_mse: 0.0746
Epoch 86/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0648 - mse: 0.0648
2600/3021 [========================>.....] - ETA: 0s - loss: 0.0766 - mse: 0.0766
3021/3021 [==============================] - 0s 151us/sample - loss: 0.0738 - mse: 0.0738 - val_loss: 0.0650 - val_mse: 0.0650
Epoch 87/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0521 - mse: 0.0521
2600/3021 [========================>.....] - ETA: 0s - loss: 0.0773 - mse: 0.0773
3021/3021 [==============================] - 0s 156us/sample - loss: 0.0754 - mse: 0.0754 - val_loss: 0.0527 - val_mse: 0.0527
Epoch 88/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0370 - mse: 0.0370
2400/3021 [======================>.......] - ETA: 0s - loss: 0.0501 - mse: 0.0501
3021/3021 [==============================] - 0s 162us/sample - loss: 0.0479 - mse: 0.0479 - val_loss: 0.0451 - val_mse: 0.0451
Epoch 89/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0514 - mse: 0.0514
2000/3021 [==================>...........] - ETA: 0s - loss: 0.0635 - mse: 0.0635
3021/3021 [==============================] - 0s 155us/sample - loss: 0.0605 - mse: 0.0605 - val_loss: 0.0552 - val_mse: 0.0552
Epoch 90/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0561 - mse: 0.0561
2600/3021 [========================>.....] - ETA: 0s - loss: 0.0520 - mse: 0.0520
3021/3021 [==============================] - 0s 157us/sample - loss: 0.0551 - mse: 0.0551 - val_loss: 0.0404 - val_mse: 0.0404
Epoch 91/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0498 - mse: 0.0498
1600/3021 [==============>...............] - ETA: 0s - loss: 0.0670 - mse: 0.0670
3021/3021 [==============================] - 0s 156us/sample - loss: 0.0605 - mse: 0.0605 - val_loss: 0.0535 - val_mse: 0.0535
Epoch 92/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0535 - mse: 0.0535
2600/3021 [========================>.....] - ETA: 0s - loss: 0.0575 - mse: 0.0575
3021/3021 [==============================] - 0s 165us/sample - loss: 0.0570 - mse: 0.0570 - val_loss: 0.0863 - val_mse: 0.0863
Epoch 93/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0992 - mse: 0.0992
2200/3021 [====================>.........] - ETA: 0s - loss: 0.0615 - mse: 0.0615
3021/3021 [==============================] - 0s 160us/sample - loss: 0.0561 - mse: 0.0561 - val_loss: 0.0586 - val_mse: 0.0586
Epoch 94/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0583 - mse: 0.0583
2600/3021 [========================>.....] - ETA: 0s - loss: 0.0706 - mse: 0.0706
3021/3021 [==============================] - 0s 156us/sample - loss: 0.0738 - mse: 0.0738 - val_loss: 0.0690 - val_mse: 0.0690
Epoch 95/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0642 - mse: 0.0642
2400/3021 [======================>.......] - ETA: 0s - loss: 0.0729 - mse: 0.0729
3021/3021 [==============================] - 0s 158us/sample - loss: 0.0697 - mse: 0.0697 - val_loss: 0.1391 - val_mse: 0.1391
Epoch 96/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1425 - mse: 0.1425
2600/3021 [========================>.....] - ETA: 0s - loss: 0.1026 - mse: 0.1026
3021/3021 [==============================] - 0s 162us/sample - loss: 0.0976 - mse: 0.0976 - val_loss: 0.0537 - val_mse: 0.0537
Epoch 97/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0619 - mse: 0.0619
2400/3021 [======================>.......] - ETA: 0s - loss: 0.0697 - mse: 0.0697
3021/3021 [==============================] - 0s 151us/sample - loss: 0.0690 - mse: 0.0690 - val_loss: 0.0544 - val_mse: 0.0544
Epoch 98/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0641 - mse: 0.0641
2800/3021 [==========================>...] - ETA: 0s - loss: 0.0643 - mse: 0.0643
3021/3021 [==============================] - 0s 153us/sample - loss: 0.0636 - mse: 0.0636 - val_loss: 0.0510 - val_mse: 0.0510
Epoch 99/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0566 - mse: 0.0566
2000/3021 [==================>...........] - ETA: 0s - loss: 0.0497 - mse: 0.0497
3021/3021 [==============================] - 0s 155us/sample - loss: 0.0463 - mse: 0.0463 - val_loss: 0.0662 - val_mse: 0.0662
Epoch 100/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0548 - mse: 0.0548
2800/3021 [==========================>...] - ETA: 0s - loss: 0.0627 - mse: 0.0627
3021/3021 [==============================] - 0s 160us/sample - loss: 0.0619 - mse: 0.0619 - val_loss: 0.0659 - val_mse: 0.0659Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-05-04T01-09-55Z
Training run 37/46 (flags = list(128, 392, 0.01, 100, 100, "sigmoid", "tanh", 0.1, 0.1))
Using run directory runs/2020-05-04T01-10-48Z
> FLAGS <- flags(
+ flag_numeric("nodes1", 128),
+ flag_numeric("nodes2", 128),
+ flag_numeric("batch_size", 100),
+ flag_string("activation1" .... [TRUNCATED]
> model = keras_model_sequential()
> model %>%
+ layer_dense(units=FLAGS$nodes1, activation=FLAGS$activation1, input_shape=dim(efw_train2)[2]) %>%
+ layer_dropout(FLAGS$dropout1) %> .... [TRUNCATED]
> model %>% compile(
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ loss = 'mse',
+ metrics = c('mse')
+ )
> model %>% fit(
+ as.matrix(efw_train2), train2Label,
+ epochs=FLAGS$epochs,
+ batch_size=FLAGS$batch_size,
+ validation_data=list(as.matrix( .... [TRUNCATED]
Train on 3021 samples, validate on 334 samples
Epoch 1/100
100/3021 [..............................] - ETA: 7s - loss: 50.4544 - mse: 50.4544
2300/3021 [=====================>........] - ETA: 0s - loss: 10.4922 - mse: 10.4922
3021/3021 [==============================] - 1s 258us/sample - loss: 8.2742 - mse: 8.2742 - val_loss: 0.2079 - val_mse: 0.2079
Epoch 2/100
100/3021 [..............................] - ETA: 0s - loss: 0.2314 - mse: 0.2314
2200/3021 [====================>.........] - ETA: 0s - loss: 0.4012 - mse: 0.4012
3021/3021 [==============================] - 0s 158us/sample - loss: 0.3575 - mse: 0.3575 - val_loss: 0.0896 - val_mse: 0.0896
Epoch 3/100
100/3021 [..............................] - ETA: 0s - loss: 0.2073 - mse: 0.2073
2200/3021 [====================>.........] - ETA: 0s - loss: 0.1511 - mse: 0.1511
3021/3021 [==============================] - 0s 162us/sample - loss: 0.1432 - mse: 0.1432 - val_loss: 0.0525 - val_mse: 0.0525
Epoch 4/100
100/3021 [..............................] - ETA: 0s - loss: 0.1074 - mse: 0.1074
2000/3021 [==================>...........] - ETA: 0s - loss: 0.1266 - mse: 0.1266
3021/3021 [==============================] - 0s 156us/sample - loss: 0.1254 - mse: 0.1254 - val_loss: 0.0465 - val_mse: 0.0465
Epoch 5/100
100/3021 [..............................] - ETA: 0s - loss: 0.1267 - mse: 0.1267
2100/3021 [===================>..........] - ETA: 0s - loss: 0.1226 - mse: 0.1226
3021/3021 [==============================] - 1s 166us/sample - loss: 0.1202 - mse: 0.1202 - val_loss: 0.0412 - val_mse: 0.0412
Epoch 6/100
100/3021 [..............................] - ETA: 0s - loss: 0.1356 - mse: 0.1356
1200/3021 [==========>...................] - ETA: 0s - loss: 0.1217 - mse: 0.1217
3021/3021 [==============================] - 0s 162us/sample - loss: 0.1194 - mse: 0.1194 - val_loss: 0.0439 - val_mse: 0.0439
Epoch 7/100
100/3021 [..............................] - ETA: 0s - loss: 0.1367 - mse: 0.1367
2200/3021 [====================>.........] - ETA: 0s - loss: 0.1088 - mse: 0.1088
3021/3021 [==============================] - 0s 159us/sample - loss: 0.1136 - mse: 0.1136 - val_loss: 0.0446 - val_mse: 0.0446
Epoch 8/100
100/3021 [..............................] - ETA: 0s - loss: 0.0936 - mse: 0.0936
1500/3021 [=============>................] - ETA: 0s - loss: 0.1086 - mse: 0.1086
3021/3021 [==============================] - 1s 166us/sample - loss: 0.1119 - mse: 0.1119 - val_loss: 0.0393 - val_mse: 0.0393
Epoch 9/100
100/3021 [..............................] - ETA: 0s - loss: 0.1796 - mse: 0.1796
1500/3021 [=============>................] - ETA: 0s - loss: 0.1101 - mse: 0.1101
3021/3021 [==============================] - 1s 167us/sample - loss: 0.1118 - mse: 0.1118 - val_loss: 0.0406 - val_mse: 0.0406
Epoch 10/100
100/3021 [..............................] - ETA: 0s - loss: 0.1388 - mse: 0.1388
2000/3021 [==================>...........] - ETA: 0s - loss: 0.1154 - mse: 0.1154
3021/3021 [==============================] - 0s 151us/sample - loss: 0.1118 - mse: 0.1118 - val_loss: 0.0408 - val_mse: 0.0408
Epoch 11/100
100/3021 [..............................] - ETA: 0s - loss: 0.1031 - mse: 0.1031
2100/3021 [===================>..........] - ETA: 0s - loss: 0.1035 - mse: 0.1035
3021/3021 [==============================] - 0s 156us/sample - loss: 0.1057 - mse: 0.1057 - val_loss: 0.0446 - val_mse: 0.0446
Epoch 12/100
100/3021 [..............................] - ETA: 0s - loss: 0.0825 - mse: 0.0825
2000/3021 [==================>...........] - ETA: 0s - loss: 0.1132 - mse: 0.1132
3021/3021 [==============================] - 0s 165us/sample - loss: 0.1079 - mse: 0.1079 - val_loss: 0.0396 - val_mse: 0.0396
Epoch 13/100
100/3021 [..............................] - ETA: 0s - loss: 0.0868 - mse: 0.0868
1500/3021 [=============>................] - ETA: 0s - loss: 0.1029 - mse: 0.1029
3021/3021 [==============================] - 0s 159us/sample - loss: 0.1037 - mse: 0.1037 - val_loss: 0.0396 - val_mse: 0.0396
Epoch 14/100
100/3021 [..............................] - ETA: 0s - loss: 0.0771 - mse: 0.0771
2400/3021 [======================>.......] - ETA: 0s - loss: 0.0956 - mse: 0.0956
3021/3021 [==============================] - 0s 148us/sample - loss: 0.0959 - mse: 0.0959 - val_loss: 0.0359 - val_mse: 0.0359
Epoch 15/100
100/3021 [..............................] - ETA: 0s - loss: 0.1205 - mse: 0.1205
1600/3021 [==============>...............] - ETA: 0s - loss: 0.1043 - mse: 0.1043
3021/3021 [==============================] - 1s 171us/sample - loss: 0.1073 - mse: 0.1073 - val_loss: 0.0452 - val_mse: 0.0452
Epoch 16/100
100/3021 [..............................] - ETA: 0s - loss: 0.0990 - mse: 0.0990
1900/3021 [=================>............] - ETA: 0s - loss: 0.1025 - mse: 0.1025
3021/3021 [==============================] - 1s 166us/sample - loss: 0.0986 - mse: 0.0986 - val_loss: 0.0377 - val_mse: 0.0377
Epoch 17/100
100/3021 [..............................] - ETA: 0s - loss: 0.0989 - mse: 0.0989
2200/3021 [====================>.........] - ETA: 0s - loss: 0.0845 - mse: 0.0845
3021/3021 [==============================] - 0s 162us/sample - loss: 0.0888 - mse: 0.0888 - val_loss: 0.0432 - val_mse: 0.0432
Epoch 18/100
100/3021 [..............................] - ETA: 0s - loss: 0.1037 - mse: 0.1037
1000/3021 [========>.....................] - ETA: 0s - loss: 0.0957 - mse: 0.0957
3021/3021 [==============================] - 0s 164us/sample - loss: 0.0913 - mse: 0.0913 - val_loss: 0.0435 - val_mse: 0.0435
Epoch 19/100
100/3021 [..............................] - ETA: 0s - loss: 0.1258 - mse: 0.1258
2100/3021 [===================>..........] - ETA: 0s - loss: 0.0896 - mse: 0.0896
3021/3021 [==============================] - 0s 158us/sample - loss: 0.0934 - mse: 0.0934 - val_loss: 0.0398 - val_mse: 0.0398
Epoch 20/100
100/3021 [..............................] - ETA: 0s - loss: 0.0738 - mse: 0.0738
1900/3021 [=================>............] - ETA: 0s - loss: 0.0833 - mse: 0.0833
3021/3021 [==============================] - 0s 156us/sample - loss: 0.0872 - mse: 0.0872 - val_loss: 0.0384 - val_mse: 0.0384
Epoch 21/100
100/3021 [..............................] - ETA: 0s - loss: 0.0952 - mse: 0.0952
2500/3021 [=======================>......] - ETA: 0s - loss: 0.0861 - mse: 0.0861
3021/3021 [==============================] - 1s 169us/sample - loss: 0.0892 - mse: 0.0892 - val_loss: 0.0358 - val_mse: 0.0358
Epoch 22/100
100/3021 [..............................] - ETA: 0s - loss: 0.1101 - mse: 0.1101
1200/3021 [==========>...................] - ETA: 0s - loss: 0.0893 - mse: 0.0893
3021/3021 [==============================] - 1s 168us/sample - loss: 0.0861 - mse: 0.0861 - val_loss: 0.0368 - val_mse: 0.0368
Epoch 23/100
100/3021 [..............................] - ETA: 0s - loss: 0.0739 - mse: 0.0739
1500/3021 [=============>................] - ETA: 0s - loss: 0.0821 - mse: 0.0821
3021/3021 [==============================] - 0s 161us/sample - loss: 0.0860 - mse: 0.0860 - val_loss: 0.0335 - val_mse: 0.0335
Epoch 24/100
100/3021 [..............................] - ETA: 0s - loss: 0.0652 - mse: 0.0652
2400/3021 [======================>.......] - ETA: 0s - loss: 0.0797 - mse: 0.0797
3021/3021 [==============================] - 0s 156us/sample - loss: 0.0804 - mse: 0.0804 - val_loss: 0.0404 - val_mse: 0.0404
Epoch 25/100
100/3021 [..............................] - ETA: 0s - loss: 0.1163 - mse: 0.1163
1400/3021 [============>.................] - ETA: 0s - loss: 0.0843 - mse: 0.0843
3021/3021 [==============================] - 0s 157us/sample - loss: 0.0812 - mse: 0.0812 - val_loss: 0.0418 - val_mse: 0.0418
Epoch 26/100
100/3021 [..............................] - ETA: 0s - loss: 0.0596 - mse: 0.0596
2400/3021 [======================>.......] - ETA: 0s - loss: 0.0777 - mse: 0.0777
3021/3021 [==============================] - 0s 151us/sample - loss: 0.0774 - mse: 0.0774 - val_loss: 0.0353 - val_mse: 0.0353
Epoch 27/100
100/3021 [..............................] - ETA: 0s - loss: 0.0777 - mse: 0.0777
1900/3021 [=================>............] - ETA: 0s - loss: 0.0746 - mse: 0.0746
3021/3021 [==============================] - 1s 171us/sample - loss: 0.0787 - mse: 0.0787 - val_loss: 0.0371 - val_mse: 0.0371
Epoch 28/100
100/3021 [..............................] - ETA: 0s - loss: 0.1012 - mse: 0.1012
1800/3021 [================>.............] - ETA: 0s - loss: 0.0785 - mse: 0.0785
3021/3021 [==============================] - 1s 169us/sample - loss: 0.0789 - mse: 0.0789 - val_loss: 0.0401 - val_mse: 0.0401
Epoch 29/100
100/3021 [..............................] - ETA: 0s - loss: 0.0728 - mse: 0.0728
1400/3021 [============>.................] - ETA: 0s - loss: 0.0845 - mse: 0.0845
3021/3021 [==============================] - 1s 174us/sample - loss: 0.0801 - mse: 0.0801 - val_loss: 0.0355 - val_mse: 0.0355
Epoch 30/100
100/3021 [..............................] - ETA: 0s - loss: 0.0860 - mse: 0.0860
1400/3021 [============>.................] - ETA: 0s - loss: 0.0803 - mse: 0.0803
3021/3021 [==============================] - 1s 169us/sample - loss: 0.0775 - mse: 0.0775 - val_loss: 0.0383 - val_mse: 0.0383
Epoch 31/100
100/3021 [..............................] - ETA: 0s - loss: 0.1119 - mse: 0.1119
1200/3021 [==========>...................] - ETA: 0s - loss: 0.0811 - mse: 0.0811
3021/3021 [==============================] - 0s 165us/sample - loss: 0.0780 - mse: 0.0780 - val_loss: 0.0337 - val_mse: 0.0337
Epoch 32/100
100/3021 [..............................] - ETA: 0s - loss: 0.0618 - mse: 0.0618
2100/3021 [===================>..........] - ETA: 0s - loss: 0.0726 - mse: 0.0726
3021/3021 [==============================] - 0s 160us/sample - loss: 0.0765 - mse: 0.0765 - val_loss: 0.0362 - val_mse: 0.0362
Epoch 33/100
100/3021 [..............................] - ETA: 0s - loss: 0.1089 - mse: 0.1089
1200/3021 [==========>...................] - ETA: 0s - loss: 0.0731 - mse: 0.0731
3021/3021 [==============================] - 0s 162us/sample - loss: 0.0736 - mse: 0.0736 - val_loss: 0.0351 - val_mse: 0.0351
Epoch 34/100
100/3021 [..............................] - ETA: 0s - loss: 0.0781 - mse: 0.0781
1400/3021 [============>.................] - ETA: 0s - loss: 0.0696 - mse: 0.0696
2900/3021 [===========================>..] - ETA: 0s - loss: 0.0716 - mse: 0.0716
3021/3021 [==============================] - 0s 162us/sample - loss: 0.0715 - mse: 0.0715 - val_loss: 0.0365 - val_mse: 0.0365
Epoch 35/100
100/3021 [..............................] - ETA: 0s - loss: 0.0730 - mse: 0.0730
1800/3021 [================>.............] - ETA: 0s - loss: 0.0761 - mse: 0.0761
3021/3021 [==============================] - 0s 147us/sample - loss: 0.0774 - mse: 0.0774 - val_loss: 0.0409 - val_mse: 0.0409
Epoch 36/100
100/3021 [..............................] - ETA: 0s - loss: 0.0687 - mse: 0.0687
2000/3021 [==================>...........] - ETA: 0s - loss: 0.0751 - mse: 0.0751
3021/3021 [==============================] - 0s 152us/sample - loss: 0.0716 - mse: 0.0716 - val_loss: 0.0364 - val_mse: 0.0364
Epoch 37/100
100/3021 [..............................] - ETA: 0s - loss: 0.0569 - mse: 0.0569
1900/3021 [=================>............] - ETA: 0s - loss: 0.0703 - mse: 0.0703
3021/3021 [==============================] - 0s 155us/sample - loss: 0.0671 - mse: 0.0671 - val_loss: 0.0337 - val_mse: 0.0337
Epoch 38/100
100/3021 [..............................] - ETA: 0s - loss: 0.0585 - mse: 0.0585
2200/3021 [====================>.........] - ETA: 0s - loss: 0.0674 - mse: 0.0674
3021/3021 [==============================] - 0s 156us/sample - loss: 0.0681 - mse: 0.0681 - val_loss: 0.0327 - val_mse: 0.0327
Epoch 39/100
100/3021 [..............................] - ETA: 0s - loss: 0.0549 - mse: 0.0549
1200/3021 [==========>...................] - ETA: 0s - loss: 0.0646 - mse: 0.0646
3021/3021 [==============================] - 0s 159us/sample - loss: 0.0640 - mse: 0.0640 - val_loss: 0.0353 - val_mse: 0.0353
Epoch 40/100
100/3021 [..............................] - ETA: 0s - loss: 0.0860 - mse: 0.0860
2300/3021 [=====================>........] - ETA: 0s - loss: 0.0684 - mse: 0.0684
3021/3021 [==============================] - 0s 155us/sample - loss: 0.0661 - mse: 0.0661 - val_loss: 0.0373 - val_mse: 0.0373
Epoch 41/100
100/3021 [..............................] - ETA: 0s - loss: 0.0667 - mse: 0.0667
2000/3021 [==================>...........] - ETA: 0s - loss: 0.0655 - mse: 0.0655
3021/3021 [==============================] - 0s 154us/sample - loss: 0.0657 - mse: 0.0657 - val_loss: 0.0389 - val_mse: 0.0389
Epoch 42/100
100/3021 [..............................] - ETA: 0s - loss: 0.0556 - mse: 0.0556
2000/3021 [==================>...........] - ETA: 0s - loss: 0.0663 - mse: 0.0663
3021/3021 [==============================] - 1s 168us/sample - loss: 0.0643 - mse: 0.0643 - val_loss: 0.0353 - val_mse: 0.0353
Epoch 43/100
100/3021 [..............................] - ETA: 0s - loss: 0.0677 - mse: 0.0677
1900/3021 [=================>............] - ETA: 0s - loss: 0.0615 - mse: 0.0615
3021/3021 [==============================] - 0s 159us/sample - loss: 0.0610 - mse: 0.0610 - val_loss: 0.0374 - val_mse: 0.0374
Epoch 44/100
100/3021 [..............................] - ETA: 0s - loss: 0.0502 - mse: 0.0502
2000/3021 [==================>...........] - ETA: 0s - loss: 0.0610 - mse: 0.0610
3021/3021 [==============================] - 0s 159us/sample - loss: 0.0625 - mse: 0.0625 - val_loss: 0.0346 - val_mse: 0.0346
Epoch 45/100
100/3021 [..............................] - ETA: 0s - loss: 0.0727 - mse: 0.0727
1400/3021 [============>.................] - ETA: 0s - loss: 0.0612 - mse: 0.0612
3021/3021 [==============================] - 0s 164us/sample - loss: 0.0612 - mse: 0.0612 - val_loss: 0.0335 - val_mse: 0.0335
Epoch 46/100
100/3021 [..............................] - ETA: 0s - loss: 0.0625 - mse: 0.0625
2200/3021 [====================>.........] - ETA: 0s - loss: 0.0696 - mse: 0.0696
3021/3021 [==============================] - 0s 155us/sample - loss: 0.0676 - mse: 0.0676 - val_loss: 0.0366 - val_mse: 0.0366
Epoch 47/100
100/3021 [..............................] - ETA: 0s - loss: 0.0638 - mse: 0.0638
1100/3021 [=========>....................] - ETA: 0s - loss: 0.0649 - mse: 0.0649
3021/3021 [==============================] - 0s 163us/sample - loss: 0.0613 - mse: 0.0613 - val_loss: 0.0320 - val_mse: 0.0320
Epoch 48/100
100/3021 [..............................] - ETA: 0s - loss: 0.0559 - mse: 0.0559
2000/3021 [==================>...........] - ETA: 0s - loss: 0.0597 - mse: 0.0597
3021/3021 [==============================] - 0s 162us/sample - loss: 0.0606 - mse: 0.0606 - val_loss: 0.0374 - val_mse: 0.0374
Epoch 49/100
100/3021 [..............................] - ETA: 0s - loss: 0.0550 - mse: 0.0550
2200/3021 [====================>.........] - ETA: 0s - loss: 0.0598 - mse: 0.0598
3021/3021 [==============================] - 0s 154us/sample - loss: 0.0593 - mse: 0.0593 - val_loss: 0.0336 - val_mse: 0.0336
Epoch 50/100
100/3021 [..............................] - ETA: 0s - loss: 0.0625 - mse: 0.0625
2200/3021 [====================>.........] - ETA: 0s - loss: 0.0612 - mse: 0.0612
3021/3021 [==============================] - 0s 155us/sample - loss: 0.0614 - mse: 0.0614 - val_loss: 0.0335 - val_mse: 0.0335
Epoch 51/100
100/3021 [..............................] - ETA: 0s - loss: 0.0578 - mse: 0.0578
1500/3021 [=============>................] - ETA: 0s - loss: 0.0591 - mse: 0.0591
3021/3021 [==============================] - 0s 160us/sample - loss: 0.0605 - mse: 0.0605 - val_loss: 0.0329 - val_mse: 0.0329
Epoch 52/100
100/3021 [..............................] - ETA: 0s - loss: 0.0694 - mse: 0.0694
1800/3021 [================>.............] - ETA: 0s - loss: 0.0590 - mse: 0.0590
3021/3021 [==============================] - 0s 164us/sample - loss: 0.0595 - mse: 0.0595 - val_loss: 0.0369 - val_mse: 0.0369
Epoch 53/100
100/3021 [..............................] - ETA: 0s - loss: 0.0710 - mse: 0.0710
1400/3021 [============>.................] - ETA: 0s - loss: 0.0631 - mse: 0.0631
3021/3021 [==============================] - 0s 165us/sample - loss: 0.0580 - mse: 0.0580 - val_loss: 0.0346 - val_mse: 0.0346
Epoch 54/100
100/3021 [..............................] - ETA: 0s - loss: 0.0558 - mse: 0.0558
1300/3021 [===========>..................] - ETA: 0s - loss: 0.0629 - mse: 0.0629
3021/3021 [==============================] - 0s 164us/sample - loss: 0.0596 - mse: 0.0596 - val_loss: 0.0373 - val_mse: 0.0373
Epoch 55/100
100/3021 [..............................] - ETA: 0s - loss: 0.0550 - mse: 0.0550
1600/3021 [==============>...............] - ETA: 0s - loss: 0.0578 - mse: 0.0578
3021/3021 [==============================] - 0s 153us/sample - loss: 0.0578 - mse: 0.0578 - val_loss: 0.0353 - val_mse: 0.0353
Epoch 56/100
100/3021 [..............................] - ETA: 0s - loss: 0.0560 - mse: 0.0560
1900/3021 [=================>............] - ETA: 0s - loss: 0.0562 - mse: 0.0562
3021/3021 [==============================] - 0s 159us/sample - loss: 0.0573 - mse: 0.0573 - val_loss: 0.0339 - val_mse: 0.0339
Epoch 57/100
100/3021 [..............................] - ETA: 0s - loss: 0.0470 - mse: 0.0470
1800/3021 [================>.............] - ETA: 0s - loss: 0.0540 - mse: 0.0540
3021/3021 [==============================] - 0s 153us/sample - loss: 0.0569 - mse: 0.0569 - val_loss: 0.0326 - val_mse: 0.0326
Epoch 58/100
100/3021 [..............................] - ETA: 0s - loss: 0.0539 - mse: 0.0539
2000/3021 [==================>...........] - ETA: 0s - loss: 0.0555 - mse: 0.0555
3021/3021 [==============================] - 0s 156us/sample - loss: 0.0565 - mse: 0.0565 - val_loss: 0.0391 - val_mse: 0.0391
Epoch 59/100
100/3021 [..............................] - ETA: 0s - loss: 0.0545 - mse: 0.0545
2100/3021 [===================>..........] - ETA: 0s - loss: 0.0557 - mse: 0.0557
3021/3021 [==============================] - 0s 163us/sample - loss: 0.0544 - mse: 0.0544 - val_loss: 0.0365 - val_mse: 0.0365
Epoch 60/100
100/3021 [..............................] - ETA: 0s - loss: 0.0607 - mse: 0.0607
1500/3021 [=============>................] - ETA: 0s - loss: 0.0530 - mse: 0.0530
3021/3021 [==============================] - 0s 158us/sample - loss: 0.0541 - mse: 0.0541 - val_loss: 0.0465 - val_mse: 0.0465
Epoch 61/100
100/3021 [..............................] - ETA: 0s - loss: 0.0700 - mse: 0.0700
2400/3021 [======================>.......] - ETA: 0s - loss: 0.0586 - mse: 0.0586
3021/3021 [==============================] - 0s 152us/sample - loss: 0.0575 - mse: 0.0575 - val_loss: 0.0367 - val_mse: 0.0367
Epoch 62/100
100/3021 [..............................] - ETA: 0s - loss: 0.0532 - mse: 0.0532
1100/3021 [=========>....................] - ETA: 0s - loss: 0.0627 - mse: 0.0627
3021/3021 [==============================] - 0s 157us/sample - loss: 0.0590 - mse: 0.0590 - val_loss: 0.0329 - val_mse: 0.0329
Epoch 63/100
100/3021 [..............................] - ETA: 0s - loss: 0.0454 - mse: 0.0454
2300/3021 [=====================>........] - ETA: 0s - loss: 0.0554 - mse: 0.0554
3021/3021 [==============================] - 0s 150us/sample - loss: 0.0547 - mse: 0.0547 - val_loss: 0.0315 - val_mse: 0.0315
Epoch 64/100
100/3021 [..............................] - ETA: 0s - loss: 0.0564 - mse: 0.0564
1700/3021 [===============>..............] - ETA: 0s - loss: 0.0533 - mse: 0.0533
3021/3021 [==============================] - 0s 153us/sample - loss: 0.0537 - mse: 0.0537 - val_loss: 0.0334 - val_mse: 0.0334
Epoch 65/100
100/3021 [..............................] - ETA: 0s - loss: 0.0508 - mse: 0.0508
2300/3021 [=====================>........] - ETA: 0s - loss: 0.0524 - mse: 0.0524
3021/3021 [==============================] - 0s 157us/sample - loss: 0.0523 - mse: 0.0523 - val_loss: 0.0318 - val_mse: 0.0318
Epoch 66/100
100/3021 [..............................] - ETA: 0s - loss: 0.0502 - mse: 0.0502
1100/3021 [=========>....................] - ETA: 0s - loss: 0.0585 - mse: 0.0585
3000/3021 [============================>.] - ETA: 0s - loss: 0.0551 - mse: 0.0551
3021/3021 [==============================] - 0s 163us/sample - loss: 0.0553 - mse: 0.0553 - val_loss: 0.0342 - val_mse: 0.0342
Epoch 67/100
100/3021 [..............................] - ETA: 0s - loss: 0.0631 - mse: 0.0631
2100/3021 [===================>..........] - ETA: 0s - loss: 0.0548 - mse: 0.0548
3021/3021 [==============================] - 1s 170us/sample - loss: 0.0550 - mse: 0.0550 - val_loss: 0.0353 - val_mse: 0.0353
Epoch 68/100
100/3021 [..............................] - ETA: 0s - loss: 0.0474 - mse: 0.0474
1300/3021 [===========>..................] - ETA: 0s - loss: 0.0487 - mse: 0.0487
3021/3021 [==============================] - 0s 164us/sample - loss: 0.0534 - mse: 0.0534 - val_loss: 0.0301 - val_mse: 0.0301
Epoch 69/100
100/3021 [..............................] - ETA: 0s - loss: 0.0470 - mse: 0.0470
2400/3021 [======================>.......] - ETA: 0s - loss: 0.0477 - mse: 0.0477
3021/3021 [==============================] - 0s 158us/sample - loss: 0.0493 - mse: 0.0493 - val_loss: 0.0298 - val_mse: 0.0298
Epoch 70/100
100/3021 [..............................] - ETA: 0s - loss: 0.0464 - mse: 0.0464
2200/3021 [====================>.........] - ETA: 0s - loss: 0.0518 - mse: 0.0518
3021/3021 [==============================] - 0s 156us/sample - loss: 0.0513 - mse: 0.0513 - val_loss: 0.0356 - val_mse: 0.0356
Epoch 71/100
100/3021 [..............................] - ETA: 0s - loss: 0.0797 - mse: 0.0797
2100/3021 [===================>..........] - ETA: 0s - loss: 0.0510 - mse: 0.0510
3021/3021 [==============================] - 0s 156us/sample - loss: 0.0516 - mse: 0.0516 - val_loss: 0.0340 - val_mse: 0.0340
Epoch 72/100
100/3021 [..............................] - ETA: 0s - loss: 0.0519 - mse: 0.0519
1400/3021 [============>.................] - ETA: 0s - loss: 0.0511 - mse: 0.0511
3021/3021 [==============================] - 0s 159us/sample - loss: 0.0520 - mse: 0.0520 - val_loss: 0.0407 - val_mse: 0.0407
Epoch 73/100
100/3021 [..............................] - ETA: 0s - loss: 0.0556 - mse: 0.0556
1900/3021 [=================>............] - ETA: 0s - loss: 0.0521 - mse: 0.0521
3021/3021 [==============================] - 0s 157us/sample - loss: 0.0523 - mse: 0.0523 - val_loss: 0.0321 - val_mse: 0.0321
Epoch 74/100
100/3021 [..............................] - ETA: 0s - loss: 0.0370 - mse: 0.0370
1000/3021 [========>.....................] - ETA: 0s - loss: 0.0498 - mse: 0.0498
3021/3021 [==============================] - 1s 169us/sample - loss: 0.0511 - mse: 0.0511 - val_loss: 0.0341 - val_mse: 0.0341
Epoch 75/100
100/3021 [..............................] - ETA: 0s - loss: 0.0476 - mse: 0.0476
1500/3021 [=============>................] - ETA: 0s - loss: 0.0559 - mse: 0.0559
3021/3021 [==============================] - 0s 163us/sample - loss: 0.0553 - mse: 0.0553 - val_loss: 0.0341 - val_mse: 0.0341
Epoch 76/100
100/3021 [..............................] - ETA: 0s - loss: 0.0422 - mse: 0.0422
1100/3021 [=========>....................] - ETA: 0s - loss: 0.0575 - mse: 0.0575
3021/3021 [==============================] - 0s 160us/sample - loss: 0.0544 - mse: 0.0544 - val_loss: 0.0321 - val_mse: 0.0321
Epoch 77/100
100/3021 [..............................] - ETA: 0s - loss: 0.0666 - mse: 0.0666
2100/3021 [===================>..........] - ETA: 0s - loss: 0.0558 - mse: 0.0558
3021/3021 [==============================] - 0s 156us/sample - loss: 0.0531 - mse: 0.0531 - val_loss: 0.0317 - val_mse: 0.0317
Epoch 78/100
100/3021 [..............................] - ETA: 0s - loss: 0.0590 - mse: 0.0590
1100/3021 [=========>....................] - ETA: 0s - loss: 0.0513 - mse: 0.0513
3021/3021 [==============================] - 0s 161us/sample - loss: 0.0532 - mse: 0.0532 - val_loss: 0.0350 - val_mse: 0.0350
Epoch 79/100
100/3021 [..............................] - ETA: 0s - loss: 0.0456 - mse: 0.0456
2000/3021 [==================>...........] - ETA: 0s - loss: 0.0512 - mse: 0.0512
3021/3021 [==============================] - 0s 154us/sample - loss: 0.0506 - mse: 0.0506 - val_loss: 0.0372 - val_mse: 0.0372
Epoch 80/100
100/3021 [..............................] - ETA: 0s - loss: 0.0533 - mse: 0.0533
2100/3021 [===================>..........] - ETA: 0s - loss: 0.0514 - mse: 0.0514
3021/3021 [==============================] - 0s 157us/sample - loss: 0.0521 - mse: 0.0521 - val_loss: 0.0356 - val_mse: 0.0356
Epoch 81/100
100/3021 [..............................] - ETA: 0s - loss: 0.0500 - mse: 0.0500
1200/3021 [==========>...................] - ETA: 0s - loss: 0.0507 - mse: 0.0507
3021/3021 [==============================] - 1s 167us/sample - loss: 0.0532 - mse: 0.0532 - val_loss: 0.0369 - val_mse: 0.0369
Epoch 82/100
100/3021 [..............................] - ETA: 0s - loss: 0.0482 - mse: 0.0482
2100/3021 [===================>..........] - ETA: 0s - loss: 0.0499 - mse: 0.0499
3021/3021 [==============================] - 0s 157us/sample - loss: 0.0478 - mse: 0.0478 - val_loss: 0.0317 - val_mse: 0.0317
Epoch 83/100
100/3021 [..............................] - ETA: 0s - loss: 0.0435 - mse: 0.0435
1100/3021 [=========>....................] - ETA: 0s - loss: 0.0505 - mse: 0.0505
3021/3021 [==============================] - 0s 159us/sample - loss: 0.0507 - mse: 0.0507 - val_loss: 0.0303 - val_mse: 0.0303
Epoch 84/100
100/3021 [..............................] - ETA: 0s - loss: 0.0374 - mse: 0.0374
1300/3021 [===========>..................] - ETA: 0s - loss: 0.0475 - mse: 0.0475
3021/3021 [==============================] - 0s 159us/sample - loss: 0.0509 - mse: 0.0509 - val_loss: 0.0409 - val_mse: 0.0409
Epoch 85/100
100/3021 [..............................] - ETA: 0s - loss: 0.0591 - mse: 0.0591
1900/3021 [=================>............] - ETA: 0s - loss: 0.0535 - mse: 0.0535
3021/3021 [==============================] - 0s 149us/sample - loss: 0.0525 - mse: 0.0525 - val_loss: 0.0338 - val_mse: 0.0338
Epoch 86/100
100/3021 [..............................] - ETA: 0s - loss: 0.0434 - mse: 0.0434
2100/3021 [===================>..........] - ETA: 0s - loss: 0.0493 - mse: 0.0493
3021/3021 [==============================] - 0s 157us/sample - loss: 0.0489 - mse: 0.0489 - val_loss: 0.0311 - val_mse: 0.0311
Epoch 87/100
100/3021 [..............................] - ETA: 0s - loss: 0.0502 - mse: 0.0502
2000/3021 [==================>...........] - ETA: 0s - loss: 0.0491 - mse: 0.0491
3021/3021 [==============================] - 0s 154us/sample - loss: 0.0485 - mse: 0.0485 - val_loss: 0.0337 - val_mse: 0.0337
Epoch 88/100
100/3021 [..............................] - ETA: 0s - loss: 0.0625 - mse: 0.0625
2500/3021 [=======================>......] - ETA: 0s - loss: 0.0443 - mse: 0.0443
3021/3021 [==============================] - 1s 172us/sample - loss: 0.0453 - mse: 0.0453 - val_loss: 0.0329 - val_mse: 0.0329
Epoch 89/100
100/3021 [..............................] - ETA: 0s - loss: 0.0516 - mse: 0.0516
1700/3021 [===============>..............] - ETA: 0s - loss: 0.0505 - mse: 0.0505
3021/3021 [==============================] - 0s 160us/sample - loss: 0.0500 - mse: 0.0500 - val_loss: 0.0298 - val_mse: 0.0298
Epoch 90/100
100/3021 [..............................] - ETA: 0s - loss: 0.0577 - mse: 0.0577
2400/3021 [======================>.......] - ETA: 0s - loss: 0.0468 - mse: 0.0468
3021/3021 [==============================] - 0s 153us/sample - loss: 0.0466 - mse: 0.0466 - val_loss: 0.0318 - val_mse: 0.0318
Epoch 91/100
100/3021 [..............................] - ETA: 0s - loss: 0.0387 - mse: 0.0387
2000/3021 [==================>...........] - ETA: 0s - loss: 0.0498 - mse: 0.0498
3021/3021 [==============================] - 0s 152us/sample - loss: 0.0483 - mse: 0.0483 - val_loss: 0.0305 - val_mse: 0.0305
Epoch 92/100
100/3021 [..............................] - ETA: 0s - loss: 0.0412 - mse: 0.0412
1900/3021 [=================>............] - ETA: 0s - loss: 0.0464 - mse: 0.0464
3021/3021 [==============================] - 0s 163us/sample - loss: 0.0450 - mse: 0.0450 - val_loss: 0.0307 - val_mse: 0.0307
Epoch 93/100
100/3021 [..............................] - ETA: 0s - loss: 0.0478 - mse: 0.0478
2100/3021 [===================>..........] - ETA: 0s - loss: 0.0469 - mse: 0.0469
3021/3021 [==============================] - 0s 159us/sample - loss: 0.0480 - mse: 0.0480 - val_loss: 0.0313 - val_mse: 0.0313
Epoch 94/100
100/3021 [..............................] - ETA: 0s - loss: 0.0492 - mse: 0.0492
2100/3021 [===================>..........] - ETA: 0s - loss: 0.0511 - mse: 0.0511
3021/3021 [==============================] - 0s 159us/sample - loss: 0.0490 - mse: 0.0490 - val_loss: 0.0336 - val_mse: 0.0336
Epoch 95/100
100/3021 [..............................] - ETA: 0s - loss: 0.0536 - mse: 0.0536
2400/3021 [======================>.......] - ETA: 0s - loss: 0.0503 - mse: 0.0503
3021/3021 [==============================] - 0s 157us/sample - loss: 0.0497 - mse: 0.0497 - val_loss: 0.0391 - val_mse: 0.0391
Epoch 96/100
100/3021 [..............................] - ETA: 0s - loss: 0.0552 - mse: 0.0552
2400/3021 [======================>.......] - ETA: 0s - loss: 0.0470 - mse: 0.0470
3021/3021 [==============================] - 1s 166us/sample - loss: 0.0469 - mse: 0.0469 - val_loss: 0.0347 - val_mse: 0.0347
Epoch 97/100
100/3021 [..............................] - ETA: 0s - loss: 0.0437 - mse: 0.0437
1500/3021 [=============>................] - ETA: 0s - loss: 0.0476 - mse: 0.0476
3021/3021 [==============================] - 0s 160us/sample - loss: 0.0487 - mse: 0.0487 - val_loss: 0.0309 - val_mse: 0.0309
Epoch 98/100
100/3021 [..............................] - ETA: 0s - loss: 0.0446 - mse: 0.0446
1700/3021 [===============>..............] - ETA: 0s - loss: 0.0465 - mse: 0.0465
3021/3021 [==============================] - 0s 160us/sample - loss: 0.0459 - mse: 0.0459 - val_loss: 0.0307 - val_mse: 0.0307
Epoch 99/100
100/3021 [..............................] - ETA: 0s - loss: 0.0574 - mse: 0.0574
1900/3021 [=================>............] - ETA: 0s - loss: 0.0456 - mse: 0.0456
3021/3021 [==============================] - 0s 152us/sample - loss: 0.0453 - mse: 0.0453 - val_loss: 0.0306 - val_mse: 0.0306
Epoch 100/100
100/3021 [..............................] - ETA: 0s - loss: 0.0377 - mse: 0.0377
1800/3021 [================>.............] - ETA: 0s - loss: 0.0444 - mse: 0.0444
3021/3021 [==============================] - 0s 156us/sample - loss: 0.0429 - mse: 0.0429 - val_loss: 0.0301 - val_mse: 0.0301Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-05-04T01-10-48Z
Training run 38/46 (flags = list(128, 64, 0.001, 500, 50, "sigmoid", "sigmoid", 0.1, 0.2))
Using run directory runs/2020-05-04T01-11-41Z
> FLAGS <- flags(
+ flag_numeric("nodes1", 128),
+ flag_numeric("nodes2", 128),
+ flag_numeric("batch_size", 100),
+ flag_string("activation1" .... [TRUNCATED]
> model = keras_model_sequential()
> model %>%
+ layer_dense(units=FLAGS$nodes1, activation=FLAGS$activation1, input_shape=dim(efw_train2)[2]) %>%
+ layer_dropout(FLAGS$dropout1) %> .... [TRUNCATED]
> model %>% compile(
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ loss = 'mse',
+ metrics = c('mse')
+ )
> model %>% fit(
+ as.matrix(efw_train2), train2Label,
+ epochs=FLAGS$epochs,
+ batch_size=FLAGS$batch_size,
+ validation_data=list(as.matrix( .... [TRUNCATED]
Train on 3021 samples, validate on 334 samples
Epoch 1/50
500/3021 [===>..........................] - ETA: 1s - loss: 42.6487 - mse: 42.6487
3021/3021 [==============================] - 1s 241us/sample - loss: 39.7689 - mse: 39.7689 - val_loss: 35.7197 - val_mse: 35.7197
Epoch 2/50
500/3021 [===>..........................] - ETA: 0s - loss: 34.9850 - mse: 34.9850
3021/3021 [==============================] - 0s 137us/sample - loss: 33.1166 - mse: 33.1166 - val_loss: 29.7850 - val_mse: 29.7850
Epoch 3/50
500/3021 [===>..........................] - ETA: 0s - loss: 29.6639 - mse: 29.6639
3021/3021 [==============================] - 0s 144us/sample - loss: 27.5833 - mse: 27.5834 - val_loss: 24.5762 - val_mse: 24.5762
Epoch 4/50
500/3021 [===>..........................] - ETA: 0s - loss: 24.2658 - mse: 24.2658
3021/3021 [==============================] - 1s 249us/sample - loss: 22.5180 - mse: 22.5180 - val_loss: 20.0447 - val_mse: 20.0447
Epoch 5/50
500/3021 [===>..........................] - ETA: 0s - loss: 19.9995 - mse: 19.9995
3021/3021 [==============================] - 0s 136us/sample - loss: 18.2770 - mse: 18.2770 - val_loss: 16.1102 - val_mse: 16.1102
Epoch 6/50
500/3021 [===>..........................] - ETA: 0s - loss: 15.8154 - mse: 15.8154
3021/3021 [==============================] - 0s 139us/sample - loss: 14.5848 - mse: 14.5848 - val_loss: 12.7772 - val_mse: 12.7772
Epoch 7/50
500/3021 [===>..........................] - ETA: 0s - loss: 12.4476 - mse: 12.4476
3021/3021 [==============================] - 0s 134us/sample - loss: 11.4627 - mse: 11.4627 - val_loss: 9.9845 - val_mse: 9.9845
Epoch 8/50
500/3021 [===>..........................] - ETA: 0s - loss: 9.7221 - mse: 9.7221
3021/3021 [==============================] - 0s 136us/sample - loss: 8.8889 - mse: 8.8889 - val_loss: 7.6773 - val_mse: 7.6773
Epoch 9/50
500/3021 [===>..........................] - ETA: 0s - loss: 7.7223 - mse: 7.7223
3021/3021 [==============================] - 0s 137us/sample - loss: 6.8171 - mse: 6.8171 - val_loss: 5.8129 - val_mse: 5.8129
Epoch 10/50
500/3021 [===>..........................] - ETA: 0s - loss: 5.7461 - mse: 5.7461
3021/3021 [==============================] - 0s 130us/sample - loss: 5.1144 - mse: 5.1144 - val_loss: 4.3204 - val_mse: 4.3204
Epoch 11/50
500/3021 [===>..........................] - ETA: 0s - loss: 4.2344 - mse: 4.2344
3021/3021 [==============================] - 0s 144us/sample - loss: 3.7427 - mse: 3.7427 - val_loss: 3.1631 - val_mse: 3.1631
Epoch 12/50
500/3021 [===>..........................] - ETA: 0s - loss: 3.1842 - mse: 3.1842
3021/3021 [==============================] - 0s 140us/sample - loss: 2.7840 - mse: 2.7840 - val_loss: 2.2741 - val_mse: 2.2741
Epoch 13/50
500/3021 [===>..........................] - ETA: 0s - loss: 2.2426 - mse: 2.2426
3021/3021 [==============================] - 0s 141us/sample - loss: 1.9898 - mse: 1.9898 - val_loss: 1.6171 - val_mse: 1.6171
Epoch 14/50
500/3021 [===>..........................] - ETA: 0s - loss: 1.5451 - mse: 1.5451
3021/3021 [==============================] - 0s 136us/sample - loss: 1.4163 - mse: 1.4163 - val_loss: 1.1404 - val_mse: 1.1404
Epoch 15/50
500/3021 [===>..........................] - ETA: 0s - loss: 1.0871 - mse: 1.0871
3021/3021 [==============================] - 0s 131us/sample - loss: 0.9918 - mse: 0.9918 - val_loss: 0.7965 - val_mse: 0.7965
Epoch 16/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.8320 - mse: 0.8320
3021/3021 [==============================] - 0s 134us/sample - loss: 0.7229 - mse: 0.7229 - val_loss: 0.5516 - val_mse: 0.5516
Epoch 17/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.5513 - mse: 0.5513
3021/3021 [==============================] - 0s 139us/sample - loss: 0.5181 - mse: 0.5181 - val_loss: 0.3812 - val_mse: 0.3812
Epoch 18/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.4245 - mse: 0.4245
3021/3021 [==============================] - 0s 141us/sample - loss: 0.3752 - mse: 0.3752 - val_loss: 0.2698 - val_mse: 0.2698
Epoch 19/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.3426 - mse: 0.3426
3021/3021 [==============================] - 0s 141us/sample - loss: 0.2948 - mse: 0.2948 - val_loss: 0.1951 - val_mse: 0.1951
Epoch 20/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.2543 - mse: 0.2543
3021/3021 [==============================] - 0s 139us/sample - loss: 0.2478 - mse: 0.2478 - val_loss: 0.1469 - val_mse: 0.1469
Epoch 21/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.2247 - mse: 0.2247
3021/3021 [==============================] - 0s 142us/sample - loss: 0.2114 - mse: 0.2114 - val_loss: 0.1169 - val_mse: 0.1169
Epoch 22/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.1901 - mse: 0.1901
3021/3021 [==============================] - 0s 145us/sample - loss: 0.1891 - mse: 0.1891 - val_loss: 0.0983 - val_mse: 0.0983
Epoch 23/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.1647 - mse: 0.1647
3021/3021 [==============================] - 0s 136us/sample - loss: 0.1744 - mse: 0.1744 - val_loss: 0.0871 - val_mse: 0.0871
Epoch 24/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.1679 - mse: 0.1679
3021/3021 [==============================] - 0s 131us/sample - loss: 0.1643 - mse: 0.1643 - val_loss: 0.0800 - val_mse: 0.0800
Epoch 25/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.1743 - mse: 0.1743
3021/3021 [==============================] - 0s 135us/sample - loss: 0.1596 - mse: 0.1596 - val_loss: 0.0753 - val_mse: 0.0753
Epoch 26/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.1870 - mse: 0.1870
3021/3021 [==============================] - 0s 132us/sample - loss: 0.1726 - mse: 0.1726 - val_loss: 0.0718 - val_mse: 0.0718
Epoch 27/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.1484 - mse: 0.1484
3021/3021 [==============================] - 0s 132us/sample - loss: 0.1580 - mse: 0.1580 - val_loss: 0.0694 - val_mse: 0.0694
Epoch 28/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.1554 - mse: 0.1554
3021/3021 [==============================] - 0s 133us/sample - loss: 0.1497 - mse: 0.1497 - val_loss: 0.0675 - val_mse: 0.0675
Epoch 29/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.1406 - mse: 0.1406
3021/3021 [==============================] - 0s 129us/sample - loss: 0.1553 - mse: 0.1553 - val_loss: 0.0662 - val_mse: 0.0662
Epoch 30/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.1594 - mse: 0.1594
3021/3021 [==============================] - 0s 136us/sample - loss: 0.1576 - mse: 0.1576 - val_loss: 0.0650 - val_mse: 0.0650
Epoch 31/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.1345 - mse: 0.1345
3021/3021 [==============================] - 0s 136us/sample - loss: 0.1601 - mse: 0.1601 - val_loss: 0.0636 - val_mse: 0.0636
Epoch 32/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.1651 - mse: 0.1651
3021/3021 [==============================] - 0s 137us/sample - loss: 0.1524 - mse: 0.1524 - val_loss: 0.0626 - val_mse: 0.0626
Epoch 33/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.1617 - mse: 0.1617
3021/3021 [==============================] - 0s 137us/sample - loss: 0.1523 - mse: 0.1523 - val_loss: 0.0620 - val_mse: 0.0620
Epoch 34/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.1693 - mse: 0.1693
3021/3021 [==============================] - 0s 133us/sample - loss: 0.1547 - mse: 0.1547 - val_loss: 0.0604 - val_mse: 0.0604
Epoch 35/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.1686 - mse: 0.1686
3021/3021 [==============================] - 0s 135us/sample - loss: 0.1506 - mse: 0.1506 - val_loss: 0.0597 - val_mse: 0.0597
Epoch 36/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.1457 - mse: 0.1457
3021/3021 [==============================] - 0s 134us/sample - loss: 0.1519 - mse: 0.1519 - val_loss: 0.0586 - val_mse: 0.0586
Epoch 37/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.1568 - mse: 0.1568
3021/3021 [==============================] - 0s 131us/sample - loss: 0.1559 - mse: 0.1559 - val_loss: 0.0584 - val_mse: 0.0584
Epoch 38/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.1670 - mse: 0.1670
3021/3021 [==============================] - 0s 135us/sample - loss: 0.1523 - mse: 0.1523 - val_loss: 0.0578 - val_mse: 0.0578
Epoch 39/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.1389 - mse: 0.1389
3021/3021 [==============================] - 1s 169us/sample - loss: 0.1447 - mse: 0.1447 - val_loss: 0.0580 - val_mse: 0.0580
Epoch 40/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.1396 - mse: 0.1396
3021/3021 [==============================] - 0s 145us/sample - loss: 0.1486 - mse: 0.1486 - val_loss: 0.0571 - val_mse: 0.0571
Epoch 41/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.1422 - mse: 0.1422
3021/3021 [==============================] - 0s 137us/sample - loss: 0.1398 - mse: 0.1398 - val_loss: 0.0558 - val_mse: 0.0558
Epoch 42/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.1579 - mse: 0.1579
3021/3021 [==============================] - 0s 129us/sample - loss: 0.1476 - mse: 0.1476 - val_loss: 0.0551 - val_mse: 0.0551
Epoch 43/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.1553 - mse: 0.1553
3021/3021 [==============================] - 0s 136us/sample - loss: 0.1432 - mse: 0.1432 - val_loss: 0.0545 - val_mse: 0.0545
Epoch 44/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.1386 - mse: 0.1386
3021/3021 [==============================] - 0s 135us/sample - loss: 0.1438 - mse: 0.1438 - val_loss: 0.0536 - val_mse: 0.0536
Epoch 45/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.1450 - mse: 0.1450
3021/3021 [==============================] - 0s 136us/sample - loss: 0.1451 - mse: 0.1451 - val_loss: 0.0530 - val_mse: 0.0530
Epoch 46/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.1302 - mse: 0.1302
3021/3021 [==============================] - 0s 139us/sample - loss: 0.1410 - mse: 0.1410 - val_loss: 0.0527 - val_mse: 0.0527
Epoch 47/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.1384 - mse: 0.1384
3021/3021 [==============================] - 0s 135us/sample - loss: 0.1439 - mse: 0.1439 - val_loss: 0.0523 - val_mse: 0.0523
Epoch 48/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.1224 - mse: 0.1224
3021/3021 [==============================] - 0s 134us/sample - loss: 0.1436 - mse: 0.1436 - val_loss: 0.0521 - val_mse: 0.0521
Epoch 49/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.1560 - mse: 0.1560
3021/3021 [==============================] - 0s 143us/sample - loss: 0.1389 - mse: 0.1389 - val_loss: 0.0514 - val_mse: 0.0514
Epoch 50/50
500/3021 [===>..........................] - ETA: 0s - loss: 0.1522 - mse: 0.1522
3021/3021 [==============================] - 0s 136us/sample - loss: 0.1412 - mse: 0.1412 - val_loss: 0.0508 - val_mse: 0.0508Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-05-04T01-11-41Z
Training run 39/46 (flags = list(392, 392, 0.01, 200, 50, "tanh", "tanh", 0.5, 0.05))
Using run directory runs/2020-05-04T01-12-06Z
> FLAGS <- flags(
+ flag_numeric("nodes1", 128),
+ flag_numeric("nodes2", 128),
+ flag_numeric("batch_size", 100),
+ flag_string("activation1" .... [TRUNCATED]
> model = keras_model_sequential()
> model %>%
+ layer_dense(units=FLAGS$nodes1, activation=FLAGS$activation1, input_shape=dim(efw_train2)[2]) %>%
+ layer_dropout(FLAGS$dropout1) %> .... [TRUNCATED]
> model %>% compile(
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ loss = 'mse',
+ metrics = c('mse')
+ )
> model %>% fit(
+ as.matrix(efw_train2), train2Label,
+ epochs=FLAGS$epochs,
+ batch_size=FLAGS$batch_size,
+ validation_data=list(as.matrix( .... [TRUNCATED]
Train on 3021 samples, validate on 334 samples
Epoch 1/50
200/3021 [>.............................] - ETA: 3s - loss: 44.9217 - mse: 44.9217
3000/3021 [============================>.] - ETA: 0s - loss: 16.7202 - mse: 16.7202
3021/3021 [==============================] - 1s 252us/sample - loss: 16.6414 - mse: 16.6414 - val_loss: 4.8264 - val_mse: 4.8264
Epoch 2/50
200/3021 [>.............................] - ETA: 0s - loss: 4.9240 - mse: 4.9240
2600/3021 [========================>.....] - ETA: 0s - loss: 2.2575 - mse: 2.2575
3021/3021 [==============================] - 0s 164us/sample - loss: 2.0784 - mse: 2.0784 - val_loss: 0.5050 - val_mse: 0.5050
Epoch 3/50
200/3021 [>.............................] - ETA: 0s - loss: 1.0591 - mse: 1.0591
2600/3021 [========================>.....] - ETA: 0s - loss: 0.8570 - mse: 0.8570
3021/3021 [==============================] - 0s 157us/sample - loss: 0.8370 - mse: 0.8370 - val_loss: 0.2587 - val_mse: 0.2587
Epoch 4/50
200/3021 [>.............................] - ETA: 0s - loss: 0.6234 - mse: 0.6234
3000/3021 [============================>.] - ETA: 0s - loss: 0.5305 - mse: 0.5305
3021/3021 [==============================] - 0s 148us/sample - loss: 0.5287 - mse: 0.5287 - val_loss: 0.1501 - val_mse: 0.1501
Epoch 5/50
200/3021 [>.............................] - ETA: 0s - loss: 0.3628 - mse: 0.3628
2600/3021 [========================>.....] - ETA: 0s - loss: 0.4043 - mse: 0.4043
3021/3021 [==============================] - 0s 161us/sample - loss: 0.4005 - mse: 0.4005 - val_loss: 0.1168 - val_mse: 0.1168
Epoch 6/50
200/3021 [>.............................] - ETA: 0s - loss: 0.3911 - mse: 0.3911
1800/3021 [================>.............] - ETA: 0s - loss: 0.3763 - mse: 0.3763
3021/3021 [==============================] - 0s 155us/sample - loss: 0.3680 - mse: 0.3680 - val_loss: 0.1070 - val_mse: 0.1070
Epoch 7/50
200/3021 [>.............................] - ETA: 0s - loss: 0.3171 - mse: 0.3171
2000/3021 [==================>...........] - ETA: 0s - loss: 0.3530 - mse: 0.3530
3021/3021 [==============================] - 0s 160us/sample - loss: 0.3516 - mse: 0.3516 - val_loss: 0.0856 - val_mse: 0.0856
Epoch 8/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2955 - mse: 0.2955
2200/3021 [====================>.........] - ETA: 0s - loss: 0.3147 - mse: 0.3147
3021/3021 [==============================] - 0s 152us/sample - loss: 0.3174 - mse: 0.3174 - val_loss: 0.0927 - val_mse: 0.0927
Epoch 9/50
200/3021 [>.............................] - ETA: 0s - loss: 0.3816 - mse: 0.3816
2600/3021 [========================>.....] - ETA: 0s - loss: 0.2892 - mse: 0.2892
3021/3021 [==============================] - 0s 161us/sample - loss: 0.2919 - mse: 0.2919 - val_loss: 0.0929 - val_mse: 0.0929
Epoch 10/50
200/3021 [>.............................] - ETA: 0s - loss: 0.3429 - mse: 0.3429
2800/3021 [==========================>...] - ETA: 0s - loss: 0.2867 - mse: 0.2867
3021/3021 [==============================] - 0s 151us/sample - loss: 0.2908 - mse: 0.2908 - val_loss: 0.0873 - val_mse: 0.0873
Epoch 11/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2466 - mse: 0.2466
2000/3021 [==================>...........] - ETA: 0s - loss: 0.3119 - mse: 0.3119
3021/3021 [==============================] - 0s 148us/sample - loss: 0.3017 - mse: 0.3017 - val_loss: 0.1048 - val_mse: 0.1048
Epoch 12/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2455 - mse: 0.2455
2600/3021 [========================>.....] - ETA: 0s - loss: 0.2713 - mse: 0.2713
3021/3021 [==============================] - 0s 159us/sample - loss: 0.2665 - mse: 0.2665 - val_loss: 0.0928 - val_mse: 0.0928
Epoch 13/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2926 - mse: 0.2926
2000/3021 [==================>...........] - ETA: 0s - loss: 0.2600 - mse: 0.2600
3021/3021 [==============================] - 0s 147us/sample - loss: 0.2571 - mse: 0.2571 - val_loss: 0.0770 - val_mse: 0.0770
Epoch 14/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2460 - mse: 0.2460
2600/3021 [========================>.....] - ETA: 0s - loss: 0.2449 - mse: 0.2449
3021/3021 [==============================] - 0s 160us/sample - loss: 0.2406 - mse: 0.2406 - val_loss: 0.0708 - val_mse: 0.0708
Epoch 15/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2143 - mse: 0.2143
2800/3021 [==========================>...] - ETA: 0s - loss: 0.2405 - mse: 0.2405
3021/3021 [==============================] - 0s 147us/sample - loss: 0.2409 - mse: 0.2409 - val_loss: 0.0835 - val_mse: 0.0835
Epoch 16/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2090 - mse: 0.2090
2400/3021 [======================>.......] - ETA: 0s - loss: 0.2299 - mse: 0.2299
3021/3021 [==============================] - 0s 162us/sample - loss: 0.2277 - mse: 0.2277 - val_loss: 0.0782 - val_mse: 0.0782
Epoch 17/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1895 - mse: 0.1895
2800/3021 [==========================>...] - ETA: 0s - loss: 0.2228 - mse: 0.2228
3021/3021 [==============================] - 1s 168us/sample - loss: 0.2212 - mse: 0.2212 - val_loss: 0.0733 - val_mse: 0.0733
Epoch 18/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2088 - mse: 0.2088
2600/3021 [========================>.....] - ETA: 0s - loss: 0.2187 - mse: 0.2187
3021/3021 [==============================] - 0s 152us/sample - loss: 0.2170 - mse: 0.2170 - val_loss: 0.0839 - val_mse: 0.0839
Epoch 19/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2868 - mse: 0.2868
2600/3021 [========================>.....] - ETA: 0s - loss: 0.2387 - mse: 0.2387
3021/3021 [==============================] - 0s 150us/sample - loss: 0.2361 - mse: 0.2361 - val_loss: 0.0772 - val_mse: 0.0772
Epoch 20/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1807 - mse: 0.1807
2800/3021 [==========================>...] - ETA: 0s - loss: 0.2224 - mse: 0.2224
3021/3021 [==============================] - 0s 150us/sample - loss: 0.2234 - mse: 0.2234 - val_loss: 0.0812 - val_mse: 0.0812
Epoch 21/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1666 - mse: 0.1666
2600/3021 [========================>.....] - ETA: 0s - loss: 0.2278 - mse: 0.2278
3021/3021 [==============================] - 0s 158us/sample - loss: 0.2294 - mse: 0.2294 - val_loss: 0.0810 - val_mse: 0.0810
Epoch 22/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2010 - mse: 0.2010
2800/3021 [==========================>...] - ETA: 0s - loss: 0.2221 - mse: 0.2221
3021/3021 [==============================] - 0s 158us/sample - loss: 0.2212 - mse: 0.2212 - val_loss: 0.0836 - val_mse: 0.0836
Epoch 23/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2044 - mse: 0.2044
2600/3021 [========================>.....] - ETA: 0s - loss: 0.2218 - mse: 0.2218
3021/3021 [==============================] - 0s 151us/sample - loss: 0.2216 - mse: 0.2216 - val_loss: 0.0688 - val_mse: 0.0688
Epoch 24/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2076 - mse: 0.2076
2600/3021 [========================>.....] - ETA: 0s - loss: 0.2048 - mse: 0.2048
3021/3021 [==============================] - 1s 173us/sample - loss: 0.2063 - mse: 0.2063 - val_loss: 0.1074 - val_mse: 0.1074
Epoch 25/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1984 - mse: 0.1984
2200/3021 [====================>.........] - ETA: 0s - loss: 0.2244 - mse: 0.2244
3021/3021 [==============================] - 0s 148us/sample - loss: 0.2201 - mse: 0.2201 - val_loss: 0.0775 - val_mse: 0.0775
Epoch 26/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2304 - mse: 0.2304
2800/3021 [==========================>...] - ETA: 0s - loss: 0.2037 - mse: 0.2037
3021/3021 [==============================] - 0s 156us/sample - loss: 0.2008 - mse: 0.2008 - val_loss: 0.0654 - val_mse: 0.0654
Epoch 27/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2058 - mse: 0.2058
2000/3021 [==================>...........] - ETA: 0s - loss: 0.2119 - mse: 0.2119
3021/3021 [==============================] - 0s 149us/sample - loss: 0.2053 - mse: 0.2053 - val_loss: 0.0718 - val_mse: 0.0718
Epoch 28/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1585 - mse: 0.1585
2600/3021 [========================>.....] - ETA: 0s - loss: 0.2110 - mse: 0.2110
3021/3021 [==============================] - 0s 148us/sample - loss: 0.2152 - mse: 0.2152 - val_loss: 0.1188 - val_mse: 0.1188
Epoch 29/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1942 - mse: 0.1942
2800/3021 [==========================>...] - ETA: 0s - loss: 0.2420 - mse: 0.2420
3021/3021 [==============================] - 0s 149us/sample - loss: 0.2397 - mse: 0.2397 - val_loss: 0.0924 - val_mse: 0.0924
Epoch 30/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2564 - mse: 0.2564
2000/3021 [==================>...........] - ETA: 0s - loss: 0.2326 - mse: 0.2326
3021/3021 [==============================] - 0s 147us/sample - loss: 0.2220 - mse: 0.2220 - val_loss: 0.0886 - val_mse: 0.0886
Epoch 31/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2135 - mse: 0.2135
2800/3021 [==========================>...] - ETA: 0s - loss: 0.2163 - mse: 0.2163
3021/3021 [==============================] - 0s 157us/sample - loss: 0.2143 - mse: 0.2143 - val_loss: 0.0948 - val_mse: 0.0948
Epoch 32/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2458 - mse: 0.2458
3000/3021 [============================>.] - ETA: 0s - loss: 0.2330 - mse: 0.2330
3021/3021 [==============================] - 0s 144us/sample - loss: 0.2328 - mse: 0.2328 - val_loss: 0.0944 - val_mse: 0.0944
Epoch 33/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1900 - mse: 0.1900
2600/3021 [========================>.....] - ETA: 0s - loss: 0.2144 - mse: 0.2144
3021/3021 [==============================] - 0s 154us/sample - loss: 0.2218 - mse: 0.2218 - val_loss: 0.0988 - val_mse: 0.0988
Epoch 34/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2370 - mse: 0.2370
2600/3021 [========================>.....] - ETA: 0s - loss: 0.2095 - mse: 0.2095
3021/3021 [==============================] - 0s 150us/sample - loss: 0.2099 - mse: 0.2099 - val_loss: 0.0932 - val_mse: 0.0932
Epoch 35/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2197 - mse: 0.2197
2800/3021 [==========================>...] - ETA: 0s - loss: 0.2090 - mse: 0.2090
3021/3021 [==============================] - 0s 151us/sample - loss: 0.2124 - mse: 0.2124 - val_loss: 0.0634 - val_mse: 0.0634
Epoch 36/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1964 - mse: 0.1964
2600/3021 [========================>.....] - ETA: 0s - loss: 0.1947 - mse: 0.1947
3021/3021 [==============================] - 0s 156us/sample - loss: 0.1959 - mse: 0.1959 - val_loss: 0.0656 - val_mse: 0.0656
Epoch 37/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2349 - mse: 0.2349
2600/3021 [========================>.....] - ETA: 0s - loss: 0.1895 - mse: 0.1895
3021/3021 [==============================] - 0s 154us/sample - loss: 0.1894 - mse: 0.1894 - val_loss: 0.0534 - val_mse: 0.0534
Epoch 38/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1983 - mse: 0.1983
2800/3021 [==========================>...] - ETA: 0s - loss: 0.1826 - mse: 0.1826
3021/3021 [==============================] - 0s 153us/sample - loss: 0.1830 - mse: 0.1830 - val_loss: 0.0692 - val_mse: 0.0692
Epoch 39/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1933 - mse: 0.1933
2400/3021 [======================>.......] - ETA: 0s - loss: 0.1852 - mse: 0.1852
3021/3021 [==============================] - 0s 148us/sample - loss: 0.1805 - mse: 0.1805 - val_loss: 0.0624 - val_mse: 0.0624
Epoch 40/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1695 - mse: 0.1695
2800/3021 [==========================>...] - ETA: 0s - loss: 0.1871 - mse: 0.1871
3021/3021 [==============================] - 0s 154us/sample - loss: 0.1885 - mse: 0.1885 - val_loss: 0.0508 - val_mse: 0.0508
Epoch 41/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1774 - mse: 0.1774
2800/3021 [==========================>...] - ETA: 0s - loss: 0.1672 - mse: 0.1672
3021/3021 [==============================] - 0s 156us/sample - loss: 0.1665 - mse: 0.1665 - val_loss: 0.0582 - val_mse: 0.0582
Epoch 42/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1374 - mse: 0.1374
2800/3021 [==========================>...] - ETA: 0s - loss: 0.1803 - mse: 0.1803
3021/3021 [==============================] - 0s 154us/sample - loss: 0.1804 - mse: 0.1804 - val_loss: 0.0648 - val_mse: 0.0648
Epoch 43/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1468 - mse: 0.1468
2800/3021 [==========================>...] - ETA: 0s - loss: 0.1813 - mse: 0.1813
3021/3021 [==============================] - 0s 155us/sample - loss: 0.1799 - mse: 0.1799 - val_loss: 0.0624 - val_mse: 0.0624
Epoch 44/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1976 - mse: 0.1976
2600/3021 [========================>.....] - ETA: 0s - loss: 0.1835 - mse: 0.1835
3021/3021 [==============================] - 1s 166us/sample - loss: 0.1851 - mse: 0.1851 - val_loss: 0.0708 - val_mse: 0.0708
Epoch 45/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1807 - mse: 0.1807
2400/3021 [======================>.......] - ETA: 0s - loss: 0.1824 - mse: 0.1824
3021/3021 [==============================] - 0s 152us/sample - loss: 0.1768 - mse: 0.1768 - val_loss: 0.0712 - val_mse: 0.0712
Epoch 46/50
200/3021 [>.............................] - ETA: 0s - loss: 0.2239 - mse: 0.2239
2800/3021 [==========================>...] - ETA: 0s - loss: 0.1751 - mse: 0.1751
3021/3021 [==============================] - 0s 150us/sample - loss: 0.1764 - mse: 0.1764 - val_loss: 0.0512 - val_mse: 0.0512
Epoch 47/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1815 - mse: 0.1815
1800/3021 [================>.............] - ETA: 0s - loss: 0.1884 - mse: 0.1884
3021/3021 [==============================] - 0s 157us/sample - loss: 0.1933 - mse: 0.1933 - val_loss: 0.0584 - val_mse: 0.0584
Epoch 48/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1470 - mse: 0.1470
2400/3021 [======================>.......] - ETA: 0s - loss: 0.1849 - mse: 0.1849
3021/3021 [==============================] - 0s 159us/sample - loss: 0.1817 - mse: 0.1817 - val_loss: 0.0726 - val_mse: 0.0726
Epoch 49/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1848 - mse: 0.1848
2800/3021 [==========================>...] - ETA: 0s - loss: 0.1845 - mse: 0.1845
3021/3021 [==============================] - 0s 147us/sample - loss: 0.1839 - mse: 0.1839 - val_loss: 0.0766 - val_mse: 0.0766
Epoch 50/50
200/3021 [>.............................] - ETA: 0s - loss: 0.1702 - mse: 0.1702
2600/3021 [========================>.....] - ETA: 0s - loss: 0.1987 - mse: 0.1987
3021/3021 [==============================] - 1s 170us/sample - loss: 0.1952 - mse: 0.1952 - val_loss: 0.0827 - val_mse: 0.0827Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-05-04T01-12-06Z
Training run 40/46 (flags = list(128, 64, 0.01, 200, 100, "tanh", "tanh", 0.1, 0.5))
Using run directory runs/2020-05-04T01-12-33Z
> FLAGS <- flags(
+ flag_numeric("nodes1", 128),
+ flag_numeric("nodes2", 128),
+ flag_numeric("batch_size", 100),
+ flag_string("activation1" .... [TRUNCATED]
> model = keras_model_sequential()
> model %>%
+ layer_dense(units=FLAGS$nodes1, activation=FLAGS$activation1, input_shape=dim(efw_train2)[2]) %>%
+ layer_dropout(FLAGS$dropout1) %> .... [TRUNCATED]
> model %>% compile(
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ loss = 'mse',
+ metrics = c('mse')
+ )
> model %>% fit(
+ as.matrix(efw_train2), train2Label,
+ epochs=FLAGS$epochs,
+ batch_size=FLAGS$batch_size,
+ validation_data=list(as.matrix( .... [TRUNCATED]
Train on 3021 samples, validate on 334 samples
Epoch 1/100
200/3021 [>.............................] - ETA: 6s - loss: 43.1710 - mse: 43.1710
3021/3021 [==============================] - 1s 335us/sample - loss: 17.7260 - mse: 17.7260 - val_loss: 3.7787 - val_mse: 3.7787
Epoch 2/100
200/3021 [>.............................] - ETA: 0s - loss: 4.1664 - mse: 4.1664
3021/3021 [==============================] - 0s 146us/sample - loss: 2.3686 - mse: 2.3686 - val_loss: 1.2484 - val_mse: 1.2484
Epoch 3/100
200/3021 [>.............................] - ETA: 0s - loss: 1.4294 - mse: 1.4294
3021/3021 [==============================] - 0s 155us/sample - loss: 0.7416 - mse: 0.7416 - val_loss: 0.4458 - val_mse: 0.4458
Epoch 4/100
200/3021 [>.............................] - ETA: 0s - loss: 0.5008 - mse: 0.5008
3021/3021 [==============================] - 1s 172us/sample - loss: 0.2862 - mse: 0.2862 - val_loss: 0.1804 - val_mse: 0.1804
Epoch 5/100
200/3021 [>.............................] - ETA: 0s - loss: 0.2461 - mse: 0.2461
3021/3021 [==============================] - 0s 165us/sample - loss: 0.1946 - mse: 0.1946 - val_loss: 0.0828 - val_mse: 0.0828
Epoch 6/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1384 - mse: 0.1384
2400/3021 [======================>.......] - ETA: 0s - loss: 0.1622 - mse: 0.1622
3021/3021 [==============================] - 0s 157us/sample - loss: 0.1617 - mse: 0.1617 - val_loss: 0.0943 - val_mse: 0.0943
Epoch 7/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1488 - mse: 0.1488
2800/3021 [==========================>...] - ETA: 0s - loss: 0.1567 - mse: 0.1567
3021/3021 [==============================] - 0s 161us/sample - loss: 0.1579 - mse: 0.1579 - val_loss: 0.0954 - val_mse: 0.0954
Epoch 8/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1877 - mse: 0.1877
3021/3021 [==============================] - 0s 142us/sample - loss: 0.1463 - mse: 0.1463 - val_loss: 0.0721 - val_mse: 0.0721
Epoch 9/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1174 - mse: 0.1174
3021/3021 [==============================] - 0s 153us/sample - loss: 0.1401 - mse: 0.1401 - val_loss: 0.0667 - val_mse: 0.0667
Epoch 10/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1539 - mse: 0.1539
3000/3021 [============================>.] - ETA: 0s - loss: 0.1338 - mse: 0.1338
3021/3021 [==============================] - 0s 151us/sample - loss: 0.1343 - mse: 0.1343 - val_loss: 0.0650 - val_mse: 0.0650
Epoch 11/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1348 - mse: 0.1348
3021/3021 [==============================] - 0s 138us/sample - loss: 0.1369 - mse: 0.1369 - val_loss: 0.0756 - val_mse: 0.0756
Epoch 12/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1523 - mse: 0.1523
2600/3021 [========================>.....] - ETA: 0s - loss: 0.1312 - mse: 0.1312
3021/3021 [==============================] - 1s 209us/sample - loss: 0.1305 - mse: 0.1305 - val_loss: 0.0689 - val_mse: 0.0689
Epoch 13/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1086 - mse: 0.1086
3021/3021 [==============================] - 0s 164us/sample - loss: 0.1274 - mse: 0.1274 - val_loss: 0.0797 - val_mse: 0.0797
Epoch 14/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1155 - mse: 0.1155
3021/3021 [==============================] - 0s 144us/sample - loss: 0.1188 - mse: 0.1188 - val_loss: 0.0600 - val_mse: 0.0600
Epoch 15/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1146 - mse: 0.1146
3000/3021 [============================>.] - ETA: 0s - loss: 0.1128 - mse: 0.1128
3021/3021 [==============================] - 0s 149us/sample - loss: 0.1124 - mse: 0.1124 - val_loss: 0.0786 - val_mse: 0.0786
Epoch 16/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0923 - mse: 0.0923
3021/3021 [==============================] - 0s 165us/sample - loss: 0.1183 - mse: 0.1183 - val_loss: 0.0970 - val_mse: 0.0970
Epoch 17/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1090 - mse: 0.1090
3021/3021 [==============================] - 0s 148us/sample - loss: 0.1219 - mse: 0.1219 - val_loss: 0.0832 - val_mse: 0.0832
Epoch 18/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1395 - mse: 0.1395
3021/3021 [==============================] - 0s 151us/sample - loss: 0.1087 - mse: 0.1087 - val_loss: 0.0573 - val_mse: 0.0573
Epoch 19/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0939 - mse: 0.0939
3021/3021 [==============================] - 0s 149us/sample - loss: 0.0989 - mse: 0.0989 - val_loss: 0.0596 - val_mse: 0.0596
Epoch 20/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1113 - mse: 0.1113
3000/3021 [============================>.] - ETA: 0s - loss: 0.1247 - mse: 0.1247
3021/3021 [==============================] - 0s 156us/sample - loss: 0.1250 - mse: 0.1250 - val_loss: 0.0568 - val_mse: 0.0568
Epoch 21/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0883 - mse: 0.0883
3021/3021 [==============================] - 0s 147us/sample - loss: 0.1095 - mse: 0.1095 - val_loss: 0.0577 - val_mse: 0.0577
Epoch 22/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1184 - mse: 0.1184
3021/3021 [==============================] - 0s 155us/sample - loss: 0.1025 - mse: 0.1025 - val_loss: 0.0604 - val_mse: 0.0604
Epoch 23/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0903 - mse: 0.0903
2600/3021 [========================>.....] - ETA: 0s - loss: 0.1017 - mse: 0.1017
3021/3021 [==============================] - 0s 147us/sample - loss: 0.0990 - mse: 0.0990 - val_loss: 0.0521 - val_mse: 0.0521
Epoch 24/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0917 - mse: 0.0917
3021/3021 [==============================] - 0s 160us/sample - loss: 0.0931 - mse: 0.0931 - val_loss: 0.0734 - val_mse: 0.0734
Epoch 25/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1089 - mse: 0.1089
2200/3021 [====================>.........] - ETA: 0s - loss: 0.1085 - mse: 0.1085
3021/3021 [==============================] - 1s 182us/sample - loss: 0.1043 - mse: 0.1043 - val_loss: 0.0556 - val_mse: 0.0556
Epoch 26/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0837 - mse: 0.0837
2600/3021 [========================>.....] - ETA: 0s - loss: 0.0898 - mse: 0.0898
3021/3021 [==============================] - 0s 155us/sample - loss: 0.0898 - mse: 0.0898 - val_loss: 0.0480 - val_mse: 0.0480
Epoch 27/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0813 - mse: 0.0813
2200/3021 [====================>.........] - ETA: 0s - loss: 0.0950 - mse: 0.0950
3021/3021 [==============================] - 1s 177us/sample - loss: 0.0962 - mse: 0.0962 - val_loss: 0.0551 - val_mse: 0.0551
Epoch 28/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0941 - mse: 0.0941
3021/3021 [==============================] - 0s 163us/sample - loss: 0.1048 - mse: 0.1048 - val_loss: 0.0525 - val_mse: 0.0525
Epoch 29/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0756 - mse: 0.0756
3021/3021 [==============================] - 0s 143us/sample - loss: 0.0955 - mse: 0.0955 - val_loss: 0.0639 - val_mse: 0.0639
Epoch 30/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0982 - mse: 0.0982
3021/3021 [==============================] - 0s 142us/sample - loss: 0.0915 - mse: 0.0915 - val_loss: 0.0730 - val_mse: 0.0730
Epoch 31/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1079 - mse: 0.1079
3021/3021 [==============================] - 0s 145us/sample - loss: 0.1075 - mse: 0.1075 - val_loss: 0.0475 - val_mse: 0.0475
Epoch 32/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0729 - mse: 0.0729
3021/3021 [==============================] - 0s 143us/sample - loss: 0.1010 - mse: 0.1010 - val_loss: 0.0651 - val_mse: 0.0651
Epoch 33/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0924 - mse: 0.0924
3021/3021 [==============================] - 0s 149us/sample - loss: 0.1181 - mse: 0.1181 - val_loss: 0.1168 - val_mse: 0.1168
Epoch 34/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1508 - mse: 0.1508
3021/3021 [==============================] - 0s 149us/sample - loss: 0.1278 - mse: 0.1278 - val_loss: 0.0645 - val_mse: 0.0645
Epoch 35/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0930 - mse: 0.0930
3021/3021 [==============================] - 0s 144us/sample - loss: 0.1137 - mse: 0.1137 - val_loss: 0.0590 - val_mse: 0.0590
Epoch 36/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0880 - mse: 0.0880
3021/3021 [==============================] - 0s 147us/sample - loss: 0.0876 - mse: 0.0876 - val_loss: 0.0563 - val_mse: 0.0563
Epoch 37/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0739 - mse: 0.0739
3021/3021 [==============================] - 0s 149us/sample - loss: 0.0823 - mse: 0.0823 - val_loss: 0.0455 - val_mse: 0.0455
Epoch 38/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0703 - mse: 0.0703
3000/3021 [============================>.] - ETA: 0s - loss: 0.0808 - mse: 0.0808
3021/3021 [==============================] - 0s 143us/sample - loss: 0.0808 - mse: 0.0808 - val_loss: 0.0618 - val_mse: 0.0618
Epoch 39/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0713 - mse: 0.0713
3021/3021 [==============================] - 0s 149us/sample - loss: 0.0877 - mse: 0.0877 - val_loss: 0.0450 - val_mse: 0.0450
Epoch 40/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0609 - mse: 0.0609
3021/3021 [==============================] - 0s 139us/sample - loss: 0.0814 - mse: 0.0814 - val_loss: 0.0497 - val_mse: 0.0497
Epoch 41/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0970 - mse: 0.0970
3021/3021 [==============================] - 0s 156us/sample - loss: 0.0796 - mse: 0.0796 - val_loss: 0.0484 - val_mse: 0.0484
Epoch 42/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0713 - mse: 0.0713
2800/3021 [==========================>...] - ETA: 0s - loss: 0.0782 - mse: 0.0782
3021/3021 [==============================] - 1s 179us/sample - loss: 0.0793 - mse: 0.0793 - val_loss: 0.0519 - val_mse: 0.0519
Epoch 43/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1028 - mse: 0.1028
3000/3021 [============================>.] - ETA: 0s - loss: 0.0816 - mse: 0.0816
3021/3021 [==============================] - 0s 160us/sample - loss: 0.0818 - mse: 0.0818 - val_loss: 0.0547 - val_mse: 0.0547
Epoch 44/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0648 - mse: 0.0648
3021/3021 [==============================] - 0s 153us/sample - loss: 0.0822 - mse: 0.0822 - val_loss: 0.0422 - val_mse: 0.0422
Epoch 45/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0736 - mse: 0.0736
3000/3021 [============================>.] - ETA: 0s - loss: 0.0741 - mse: 0.0741
3021/3021 [==============================] - 0s 143us/sample - loss: 0.0739 - mse: 0.0739 - val_loss: 0.0413 - val_mse: 0.0413
Epoch 46/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0884 - mse: 0.0884
3000/3021 [============================>.] - ETA: 0s - loss: 0.0740 - mse: 0.0740
3021/3021 [==============================] - 0s 165us/sample - loss: 0.0741 - mse: 0.0741 - val_loss: 0.0507 - val_mse: 0.0507
Epoch 47/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0686 - mse: 0.0686
3000/3021 [============================>.] - ETA: 0s - loss: 0.0781 - mse: 0.0781
3021/3021 [==============================] - 0s 150us/sample - loss: 0.0784 - mse: 0.0784 - val_loss: 0.0634 - val_mse: 0.0634
Epoch 48/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0752 - mse: 0.0752
3021/3021 [==============================] - 0s 154us/sample - loss: 0.0897 - mse: 0.0897 - val_loss: 0.0890 - val_mse: 0.0890
Epoch 49/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0927 - mse: 0.0927
2800/3021 [==========================>...] - ETA: 0s - loss: 0.1240 - mse: 0.1240
3021/3021 [==============================] - 0s 147us/sample - loss: 0.1206 - mse: 0.1206 - val_loss: 0.1566 - val_mse: 0.1566
Epoch 50/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1826 - mse: 0.1826
3021/3021 [==============================] - 0s 143us/sample - loss: 0.1275 - mse: 0.1275 - val_loss: 0.0754 - val_mse: 0.0754
Epoch 51/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0898 - mse: 0.0898
3021/3021 [==============================] - 0s 147us/sample - loss: 0.0886 - mse: 0.0886 - val_loss: 0.0619 - val_mse: 0.0619
Epoch 52/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0841 - mse: 0.0841
3021/3021 [==============================] - 1s 173us/sample - loss: 0.0816 - mse: 0.0816 - val_loss: 0.0639 - val_mse: 0.0639
Epoch 53/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0957 - mse: 0.0957
3021/3021 [==============================] - 0s 156us/sample - loss: 0.0731 - mse: 0.0731 - val_loss: 0.0430 - val_mse: 0.0430
Epoch 54/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0578 - mse: 0.0578
2800/3021 [==========================>...] - ETA: 0s - loss: 0.0742 - mse: 0.0742
3021/3021 [==============================] - 0s 150us/sample - loss: 0.0735 - mse: 0.0735 - val_loss: 0.0564 - val_mse: 0.0564
Epoch 55/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0771 - mse: 0.0771
3021/3021 [==============================] - 0s 142us/sample - loss: 0.0728 - mse: 0.0728 - val_loss: 0.0520 - val_mse: 0.0520
Epoch 56/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0691 - mse: 0.0691
2600/3021 [========================>.....] - ETA: 0s - loss: 0.0785 - mse: 0.0785
3021/3021 [==============================] - 1s 167us/sample - loss: 0.0766 - mse: 0.0766 - val_loss: 0.0649 - val_mse: 0.0649
Epoch 57/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0810 - mse: 0.0810
3021/3021 [==============================] - 1s 173us/sample - loss: 0.0741 - mse: 0.0741 - val_loss: 0.0440 - val_mse: 0.0440
Epoch 58/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0633 - mse: 0.0633
2800/3021 [==========================>...] - ETA: 0s - loss: 0.0774 - mse: 0.0774
3021/3021 [==============================] - 1s 187us/sample - loss: 0.0788 - mse: 0.0788 - val_loss: 0.0413 - val_mse: 0.0413
Epoch 59/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0608 - mse: 0.0608
2200/3021 [====================>.........] - ETA: 0s - loss: 0.0713 - mse: 0.0713
3021/3021 [==============================] - 0s 160us/sample - loss: 0.0698 - mse: 0.0698 - val_loss: 0.0606 - val_mse: 0.0606
Epoch 60/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1130 - mse: 0.1130
3021/3021 [==============================] - 0s 157us/sample - loss: 0.0712 - mse: 0.0712 - val_loss: 0.0491 - val_mse: 0.0491
Epoch 61/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0754 - mse: 0.0754
2600/3021 [========================>.....] - ETA: 0s - loss: 0.0718 - mse: 0.0718
3021/3021 [==============================] - 0s 145us/sample - loss: 0.0726 - mse: 0.0726 - val_loss: 0.0505 - val_mse: 0.0505
Epoch 62/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0635 - mse: 0.0635
3021/3021 [==============================] - 0s 143us/sample - loss: 0.0649 - mse: 0.0649 - val_loss: 0.0456 - val_mse: 0.0456
Epoch 63/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0707 - mse: 0.0707
3021/3021 [==============================] - 0s 155us/sample - loss: 0.0675 - mse: 0.0675 - val_loss: 0.0473 - val_mse: 0.0473
Epoch 64/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0792 - mse: 0.0792
2200/3021 [====================>.........] - ETA: 0s - loss: 0.0719 - mse: 0.0719
3021/3021 [==============================] - 0s 143us/sample - loss: 0.0712 - mse: 0.0712 - val_loss: 0.0498 - val_mse: 0.0498
Epoch 65/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0631 - mse: 0.0631
3021/3021 [==============================] - 1s 177us/sample - loss: 0.0714 - mse: 0.0714 - val_loss: 0.0450 - val_mse: 0.0450
Epoch 66/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0548 - mse: 0.0548
2400/3021 [======================>.......] - ETA: 0s - loss: 0.0707 - mse: 0.0707
3021/3021 [==============================] - 0s 153us/sample - loss: 0.0682 - mse: 0.0682 - val_loss: 0.0456 - val_mse: 0.0456
Epoch 67/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0508 - mse: 0.0508
3021/3021 [==============================] - 0s 157us/sample - loss: 0.0743 - mse: 0.0743 - val_loss: 0.0465 - val_mse: 0.0465
Epoch 68/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0612 - mse: 0.0612
3000/3021 [============================>.] - ETA: 0s - loss: 0.0748 - mse: 0.0748
3021/3021 [==============================] - 0s 164us/sample - loss: 0.0746 - mse: 0.0746 - val_loss: 0.0402 - val_mse: 0.0402
Epoch 69/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0640 - mse: 0.0640
3021/3021 [==============================] - 0s 150us/sample - loss: 0.0654 - mse: 0.0654 - val_loss: 0.0430 - val_mse: 0.0430
Epoch 70/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0499 - mse: 0.0499
3021/3021 [==============================] - 0s 164us/sample - loss: 0.0717 - mse: 0.0717 - val_loss: 0.0631 - val_mse: 0.0631
Epoch 71/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0681 - mse: 0.0681
3021/3021 [==============================] - 0s 164us/sample - loss: 0.0839 - mse: 0.0839 - val_loss: 0.0946 - val_mse: 0.0946
Epoch 72/100
200/3021 [>.............................] - ETA: 0s - loss: 0.1254 - mse: 0.1254
3021/3021 [==============================] - 0s 153us/sample - loss: 0.0863 - mse: 0.0863 - val_loss: 0.0505 - val_mse: 0.0505
Epoch 73/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0675 - mse: 0.0675
3021/3021 [==============================] - 0s 143us/sample - loss: 0.0689 - mse: 0.0689 - val_loss: 0.0541 - val_mse: 0.0541
Epoch 74/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0690 - mse: 0.0690
3021/3021 [==============================] - 0s 148us/sample - loss: 0.0658 - mse: 0.0658 - val_loss: 0.0426 - val_mse: 0.0426
Epoch 75/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0621 - mse: 0.0621
3021/3021 [==============================] - 0s 159us/sample - loss: 0.0657 - mse: 0.0657 - val_loss: 0.0422 - val_mse: 0.0422
Epoch 76/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0602 - mse: 0.0602
3021/3021 [==============================] - 0s 145us/sample - loss: 0.0708 - mse: 0.0708 - val_loss: 0.0468 - val_mse: 0.0468
Epoch 77/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0645 - mse: 0.0645
3021/3021 [==============================] - 0s 142us/sample - loss: 0.0625 - mse: 0.0625 - val_loss: 0.0600 - val_mse: 0.0600
Epoch 78/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0837 - mse: 0.0837
3021/3021 [==============================] - 0s 163us/sample - loss: 0.0710 - mse: 0.0710 - val_loss: 0.0604 - val_mse: 0.0604
Epoch 79/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0703 - mse: 0.0703
2800/3021 [==========================>...] - ETA: 0s - loss: 0.0658 - mse: 0.0658
3021/3021 [==============================] - 1s 168us/sample - loss: 0.0658 - mse: 0.0658 - val_loss: 0.0458 - val_mse: 0.0458
Epoch 80/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0523 - mse: 0.0523
3021/3021 [==============================] - 0s 151us/sample - loss: 0.0694 - mse: 0.0694 - val_loss: 0.0529 - val_mse: 0.0529
Epoch 81/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0763 - mse: 0.0763
3021/3021 [==============================] - 0s 150us/sample - loss: 0.0743 - mse: 0.0743 - val_loss: 0.0492 - val_mse: 0.0492
Epoch 82/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0609 - mse: 0.0609
3021/3021 [==============================] - 0s 152us/sample - loss: 0.0651 - mse: 0.0651 - val_loss: 0.0412 - val_mse: 0.0412
Epoch 83/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0589 - mse: 0.0589
2400/3021 [======================>.......] - ETA: 0s - loss: 0.0623 - mse: 0.0623
3021/3021 [==============================] - 0s 145us/sample - loss: 0.0620 - mse: 0.0620 - val_loss: 0.0463 - val_mse: 0.0463
Epoch 84/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0444 - mse: 0.0444
3021/3021 [==============================] - 0s 147us/sample - loss: 0.0684 - mse: 0.0684 - val_loss: 0.0403 - val_mse: 0.0403
Epoch 85/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0536 - mse: 0.0536
3000/3021 [============================>.] - ETA: 0s - loss: 0.0606 - mse: 0.0606
3021/3021 [==============================] - 1s 178us/sample - loss: 0.0607 - mse: 0.0607 - val_loss: 0.0598 - val_mse: 0.0598
Epoch 86/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0688 - mse: 0.0688
3021/3021 [==============================] - 0s 159us/sample - loss: 0.0690 - mse: 0.0690 - val_loss: 0.0598 - val_mse: 0.0598
Epoch 87/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0765 - mse: 0.0765
3021/3021 [==============================] - 0s 151us/sample - loss: 0.0694 - mse: 0.0694 - val_loss: 0.0462 - val_mse: 0.0462
Epoch 88/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0680 - mse: 0.0680
3000/3021 [============================>.] - ETA: 0s - loss: 0.0636 - mse: 0.0636
3021/3021 [==============================] - 0s 153us/sample - loss: 0.0637 - mse: 0.0637 - val_loss: 0.0393 - val_mse: 0.0393
Epoch 89/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0558 - mse: 0.0558
3021/3021 [==============================] - 0s 150us/sample - loss: 0.0580 - mse: 0.0580 - val_loss: 0.0414 - val_mse: 0.0414
Epoch 90/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0581 - mse: 0.0581
1800/3021 [================>.............] - ETA: 0s - loss: 0.0637 - mse: 0.0637
3021/3021 [==============================] - 0s 154us/sample - loss: 0.0646 - mse: 0.0646 - val_loss: 0.0454 - val_mse: 0.0454
Epoch 91/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0600 - mse: 0.0600
3021/3021 [==============================] - 0s 151us/sample - loss: 0.0591 - mse: 0.0591 - val_loss: 0.0617 - val_mse: 0.0617
Epoch 92/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0703 - mse: 0.0703
3021/3021 [==============================] - 0s 143us/sample - loss: 0.0684 - mse: 0.0684 - val_loss: 0.0461 - val_mse: 0.0461
Epoch 93/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0598 - mse: 0.0598
3021/3021 [==============================] - 0s 151us/sample - loss: 0.0596 - mse: 0.0596 - val_loss: 0.0404 - val_mse: 0.0404
Epoch 94/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0606 - mse: 0.0606
3021/3021 [==============================] - 0s 146us/sample - loss: 0.0633 - mse: 0.0633 - val_loss: 0.0422 - val_mse: 0.0422
Epoch 95/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0685 - mse: 0.0685
3021/3021 [==============================] - 0s 151us/sample - loss: 0.0546 - mse: 0.0546 - val_loss: 0.0467 - val_mse: 0.0467
Epoch 96/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0589 - mse: 0.0589
3000/3021 [============================>.] - ETA: 0s - loss: 0.0624 - mse: 0.0624
3021/3021 [==============================] - 1s 180us/sample - loss: 0.0626 - mse: 0.0626 - val_loss: 0.0502 - val_mse: 0.0502
Epoch 97/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0588 - mse: 0.0588
3021/3021 [==============================] - 0s 151us/sample - loss: 0.0654 - mse: 0.0654 - val_loss: 0.0541 - val_mse: 0.0541
Epoch 98/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0609 - mse: 0.0609
2400/3021 [======================>.......] - ETA: 0s - loss: 0.0639 - mse: 0.0639
3021/3021 [==============================] - 0s 146us/sample - loss: 0.0620 - mse: 0.0620 - val_loss: 0.0429 - val_mse: 0.0429
Epoch 99/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0620 - mse: 0.0620
3021/3021 [==============================] - 1s 181us/sample - loss: 0.0559 - mse: 0.0559 - val_loss: 0.0495 - val_mse: 0.0495
Epoch 100/100
200/3021 [>.............................] - ETA: 0s - loss: 0.0442 - mse: 0.0442
3021/3021 [==============================] - 0s 153us/sample - loss: 0.0680 - mse: 0.0680 - val_loss: 0.0441 - val_mse: 0.0441Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-05-04T01-12-33Z
Training run 41/46 (flags = list(64, 392, 1e-04, 500, 50, "relu", "tanh", 0.2, 0.5))
Using run directory runs/2020-05-04T01-13-27Z
> FLAGS <- flags(
+ flag_numeric("nodes1", 128),
+ flag_numeric("nodes2", 128),
+ flag_numeric("batch_size", 100),
+ flag_string("activation1" .... [TRUNCATED]
> model = keras_model_sequential()
> model %>%
+ layer_dense(units=FLAGS$nodes1, activation=FLAGS$activation1, input_shape=dim(efw_train2)[2]) %>%
+ layer_dropout(FLAGS$dropout1) %> .... [TRUNCATED]
> model %>% compile(
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ loss = 'mse',
+ metrics = c('mse')
+ )
> model %>% fit(
+ as.matrix(efw_train2), train2Label,
+ epochs=FLAGS$epochs,
+ batch_size=FLAGS$batch_size,
+ validation_data=list(as.matrix( .... [TRUNCATED]
Train on 3021 samples, validate on 334 samples
Epoch 1/50
500/3021 [===>..........................] - ETA: 1s - loss: 40.1532 - mse: 40.1532
3021/3021 [==============================] - 1s 295us/sample - loss: 39.2735 - mse: 39.2735 - val_loss: 38.9610 - val_mse: 38.9610
Epoch 2/50
500/3021 [===>..........................] - ETA: 0s - loss: 39.5634 - mse: 39.5634
3021/3021 [==============================] - 0s 154us/sample - loss: 38.7750 - mse: 38.7750 - val_loss: 38.4658 - val_mse: 38.4658
Epoch 3/50
500/3021 [===>..........................] - ETA: 0s - loss: 38.0557 - mse: 38.0557
3021/3021 [==============================] - 0s 143us/sample - loss: 38.2616 - mse: 38.2616 - val_loss: 37.9772 - val_mse: 37.9772
Epoch 4/50
500/3021 [===>..........................] - ETA: 0s - loss: 37.8990 - mse: 37.8990
3021/3021 [==============================] - 0s 146us/sample - loss: 37.8042 - mse: 37.8042 - val_loss: 37.4986 - val_mse: 37.4986
Epoch 5/50
500/3021 [===>..........................] - ETA: 0s - loss: 37.3162 - mse: 37.3162
3021/3021 [==============================] - 0s 146us/sample - loss: 37.4324 - mse: 37.4324 - val_loss: 37.0273 - val_mse: 37.0273
Epoch 6/50
500/3021 [===>..........................] - ETA: 0s - loss: 37.6470 - mse: 37.6470
3021/3021 [==============================] - 0s 146us/sample - loss: 36.7916 - mse: 36.7916 - val_loss: 36.5571 - val_mse: 36.5571
Epoch 7/50
500/3021 [===>..........................] - ETA: 0s - loss: 36.9097 - mse: 36.9097
3021/3021 [==============================] - 0s 157us/sample - loss: 36.3763 - mse: 36.3763 - val_loss: 36.0889 - val_mse: 36.0889
Epoch 8/50
500/3021 [===>..........................] - ETA: 0s - loss: 36.7925 - mse: 36.7925
3021/3021 [==============================] - 0s 161us/sample - loss: 35.9103 - mse: 35.9103 - val_loss: 35.6326 - val_mse: 35.6326
Epoch 9/50
500/3021 [===>..........................] - ETA: 0s - loss: 35.2944 - mse: 35.2944
3021/3021 [==============================] - 0s 155us/sample - loss: 35.4093 - mse: 35.4093 - val_loss: 35.1838 - val_mse: 35.1838
Epoch 10/50
500/3021 [===>..........................] - ETA: 0s - loss: 35.0895 - mse: 35.0895
3021/3021 [==============================] - 0s 158us/sample - loss: 35.0486 - mse: 35.0486 - val_loss: 34.7417 - val_mse: 34.7417
Epoch 11/50
500/3021 [===>..........................] - ETA: 0s - loss: 34.6920 - mse: 34.6920
3021/3021 [==============================] - 0s 154us/sample - loss: 34.5514 - mse: 34.5514 - val_loss: 34.2967 - val_mse: 34.2967
Epoch 12/50
500/3021 [===>..........................] - ETA: 0s - loss: 34.0894 - mse: 34.0894
3021/3021 [==============================] - 0s 165us/sample - loss: 34.0735 - mse: 34.0735 - val_loss: 33.8514 - val_mse: 33.8514
Epoch 13/50
500/3021 [===>..........................] - ETA: 0s - loss: 33.3050 - mse: 33.3050
3021/3021 [==============================] - 0s 147us/sample - loss: 33.6387 - mse: 33.6387 - val_loss: 33.4121 - val_mse: 33.4121
Epoch 14/50
500/3021 [===>..........................] - ETA: 0s - loss: 33.1938 - mse: 33.1938
3021/3021 [==============================] - 0s 145us/sample - loss: 33.1514 - mse: 33.1514 - val_loss: 32.9767 - val_mse: 32.9767
Epoch 15/50
500/3021 [===>..........................] - ETA: 0s - loss: 33.1129 - mse: 33.1129
3021/3021 [==============================] - 0s 136us/sample - loss: 32.7613 - mse: 32.7613 - val_loss: 32.5445 - val_mse: 32.5445
Epoch 16/50
500/3021 [===>..........................] - ETA: 0s - loss: 32.7796 - mse: 32.7796
3021/3021 [==============================] - 0s 132us/sample - loss: 32.2722 - mse: 32.2722 - val_loss: 32.1152 - val_mse: 32.1152
Epoch 17/50
500/3021 [===>..........................] - ETA: 0s - loss: 32.2101 - mse: 32.2101
3021/3021 [==============================] - 0s 133us/sample - loss: 31.9091 - mse: 31.9091 - val_loss: 31.6894 - val_mse: 31.6894
Epoch 18/50
500/3021 [===>..........................] - ETA: 0s - loss: 31.3401 - mse: 31.3401
3021/3021 [==============================] - 0s 132us/sample - loss: 31.3948 - mse: 31.3948 - val_loss: 31.2617 - val_mse: 31.2617
Epoch 19/50
500/3021 [===>..........................] - ETA: 0s - loss: 30.5934 - mse: 30.5934
3021/3021 [==============================] - 0s 142us/sample - loss: 31.0109 - mse: 31.0109 - val_loss: 30.8311 - val_mse: 30.8311
Epoch 20/50
500/3021 [===>..........................] - ETA: 0s - loss: 30.2812 - mse: 30.2812
3021/3021 [==============================] - 0s 137us/sample - loss: 30.5435 - mse: 30.5435 - val_loss: 30.4087 - val_mse: 30.4087
Epoch 21/50
500/3021 [===>..........................] - ETA: 0s - loss: 30.4013 - mse: 30.4013
3021/3021 [==============================] - 0s 136us/sample - loss: 30.2330 - mse: 30.2330 - val_loss: 29.9921 - val_mse: 29.9921
Epoch 22/50
500/3021 [===>..........................] - ETA: 0s - loss: 30.0500 - mse: 30.0500
3021/3021 [==============================] - 0s 140us/sample - loss: 29.6800 - mse: 29.6800 - val_loss: 29.5798 - val_mse: 29.5798
Epoch 23/50
500/3021 [===>..........................] - ETA: 0s - loss: 29.6927 - mse: 29.6927
3021/3021 [==============================] - 0s 130us/sample - loss: 29.2952 - mse: 29.2952 - val_loss: 29.1672 - val_mse: 29.1672
Epoch 24/50
500/3021 [===>..........................] - ETA: 0s - loss: 28.2364 - mse: 28.2364
3021/3021 [==============================] - 0s 135us/sample - loss: 28.9325 - mse: 28.9325 - val_loss: 28.7599 - val_mse: 28.7599
Epoch 25/50
500/3021 [===>..........................] - ETA: 0s - loss: 28.7799 - mse: 28.7799
3021/3021 [==============================] - 0s 138us/sample - loss: 28.5291 - mse: 28.5291 - val_loss: 28.3482 - val_mse: 28.3482
Epoch 26/50
500/3021 [===>..........................] - ETA: 0s - loss: 28.6516 - mse: 28.6516
3021/3021 [==============================] - 0s 129us/sample - loss: 28.0959 - mse: 28.0959 - val_loss: 27.9399 - val_mse: 27.9399
Epoch 27/50
500/3021 [===>..........................] - ETA: 0s - loss: 27.4420 - mse: 27.4420
3021/3021 [==============================] - 0s 131us/sample - loss: 27.6814 - mse: 27.6814 - val_loss: 27.5350 - val_mse: 27.5350
Epoch 28/50
500/3021 [===>..........................] - ETA: 0s - loss: 27.5193 - mse: 27.5193
3021/3021 [==============================] - 0s 134us/sample - loss: 27.3177 - mse: 27.3177 - val_loss: 27.1384 - val_mse: 27.1384
Epoch 29/50
500/3021 [===>..........................] - ETA: 0s - loss: 27.2929 - mse: 27.2929
3021/3021 [==============================] - 0s 127us/sample - loss: 26.9170 - mse: 26.9170 - val_loss: 26.7369 - val_mse: 26.7369
Epoch 30/50
500/3021 [===>..........................] - ETA: 0s - loss: 25.7835 - mse: 25.7835
3021/3021 [==============================] - 1s 185us/sample - loss: 26.4234 - mse: 26.4234 - val_loss: 26.3414 - val_mse: 26.3414
Epoch 31/50
500/3021 [===>..........................] - ETA: 0s - loss: 26.9142 - mse: 26.9142
3021/3021 [==============================] - 0s 136us/sample - loss: 26.1202 - mse: 26.1202 - val_loss: 25.9487 - val_mse: 25.9487
Epoch 32/50
500/3021 [===>..........................] - ETA: 0s - loss: 26.0745 - mse: 26.0745
3021/3021 [==============================] - 0s 136us/sample - loss: 25.6828 - mse: 25.6828 - val_loss: 25.5609 - val_mse: 25.5609
Epoch 33/50
500/3021 [===>..........................] - ETA: 0s - loss: 24.9609 - mse: 24.9609
3021/3021 [==============================] - 0s 142us/sample - loss: 25.3242 - mse: 25.3242 - val_loss: 25.1742 - val_mse: 25.1742
Epoch 34/50
500/3021 [===>..........................] - ETA: 0s - loss: 25.5899 - mse: 25.5899
3021/3021 [==============================] - 0s 137us/sample - loss: 24.9032 - mse: 24.9032 - val_loss: 24.7919 - val_mse: 24.7919
Epoch 35/50
500/3021 [===>..........................] - ETA: 0s - loss: 25.7586 - mse: 25.7586
3021/3021 [==============================] - 0s 150us/sample - loss: 24.5102 - mse: 24.5102 - val_loss: 24.4143 - val_mse: 24.4143
Epoch 36/50
500/3021 [===>..........................] - ETA: 0s - loss: 24.4106 - mse: 24.4106
3021/3021 [==============================] - 0s 157us/sample - loss: 24.1890 - mse: 24.1890 - val_loss: 24.0401 - val_mse: 24.0401
Epoch 37/50
500/3021 [===>..........................] - ETA: 0s - loss: 23.8594 - mse: 23.8594
3021/3021 [==============================] - 0s 141us/sample - loss: 23.7360 - mse: 23.7360 - val_loss: 23.6725 - val_mse: 23.6725
Epoch 38/50
500/3021 [===>..........................] - ETA: 0s - loss: 23.7530 - mse: 23.7530
3021/3021 [==============================] - 0s 133us/sample - loss: 23.3735 - mse: 23.3735 - val_loss: 23.3092 - val_mse: 23.3092
Epoch 39/50
500/3021 [===>..........................] - ETA: 0s - loss: 23.8516 - mse: 23.8516
3021/3021 [==============================] - 0s 145us/sample - loss: 23.0251 - mse: 23.0251 - val_loss: 22.9500 - val_mse: 22.9500
Epoch 40/50
500/3021 [===>..........................] - ETA: 0s - loss: 23.1265 - mse: 23.1265
3021/3021 [==============================] - 0s 128us/sample - loss: 22.7766 - mse: 22.7766 - val_loss: 22.5960 - val_mse: 22.5960
Epoch 41/50
500/3021 [===>..........................] - ETA: 0s - loss: 22.1056 - mse: 22.1056
3021/3021 [==============================] - 0s 131us/sample - loss: 22.3614 - mse: 22.3614 - val_loss: 22.2463 - val_mse: 22.2463
Epoch 42/50
500/3021 [===>..........................] - ETA: 0s - loss: 21.3115 - mse: 21.3115
3021/3021 [==============================] - 0s 134us/sample - loss: 21.9546 - mse: 21.9546 - val_loss: 21.9011 - val_mse: 21.9011
Epoch 43/50
500/3021 [===>..........................] - ETA: 0s - loss: 21.9809 - mse: 21.9809
3021/3021 [==============================] - 0s 130us/sample - loss: 21.7012 - mse: 21.7012 - val_loss: 21.5628 - val_mse: 21.5628
Epoch 44/50
500/3021 [===>..........................] - ETA: 0s - loss: 21.2365 - mse: 21.2365
3021/3021 [==============================] - 0s 154us/sample - loss: 21.2573 - mse: 21.2573 - val_loss: 21.2314 - val_mse: 21.2314
Epoch 45/50
500/3021 [===>..........................] - ETA: 0s - loss: 21.2492 - mse: 21.2492
3021/3021 [==============================] - 0s 154us/sample - loss: 21.0856 - mse: 21.0856 - val_loss: 20.9071 - val_mse: 20.9071
Epoch 46/50
500/3021 [===>..........................] - ETA: 0s - loss: 21.4655 - mse: 21.4655
3021/3021 [==============================] - 0s 146us/sample - loss: 20.7484 - mse: 20.7484 - val_loss: 20.5877 - val_mse: 20.5877
Epoch 47/50
500/3021 [===>..........................] - ETA: 0s - loss: 20.9182 - mse: 20.9182
3021/3021 [==============================] - 0s 140us/sample - loss: 20.3838 - mse: 20.3838 - val_loss: 20.2736 - val_mse: 20.2736
Epoch 48/50
500/3021 [===>..........................] - ETA: 0s - loss: 20.7331 - mse: 20.7331
3021/3021 [==============================] - 0s 145us/sample - loss: 20.1971 - mse: 20.1971 - val_loss: 19.9630 - val_mse: 19.9630
Epoch 49/50
500/3021 [===>..........................] - ETA: 0s - loss: 19.7823 - mse: 19.7823
3021/3021 [==============================] - 0s 141us/sample - loss: 19.7520 - mse: 19.7520 - val_loss: 19.6614 - val_mse: 19.6614
Epoch 50/50
500/3021 [===>..........................] - ETA: 0s - loss: 19.6761 - mse: 19.6761
3021/3021 [==============================] - 0s 146us/sample - loss: 19.5003 - mse: 19.5003 - val_loss: 19.3618 - val_mse: 19.3618Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-05-04T01-13-27Z
Training run 42/46 (flags = list(392, 128, 0.01, 500, 30, "tanh", "tanh", 0.5, 0.2))
Using run directory runs/2020-05-04T01-13-53Z
> FLAGS <- flags(
+ flag_numeric("nodes1", 128),
+ flag_numeric("nodes2", 128),
+ flag_numeric("batch_size", 100),
+ flag_string("activation1" .... [TRUNCATED]
> model = keras_model_sequential()
> model %>%
+ layer_dense(units=FLAGS$nodes1, activation=FLAGS$activation1, input_shape=dim(efw_train2)[2]) %>%
+ layer_dropout(FLAGS$dropout1) %> .... [TRUNCATED]
> model %>% compile(
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ loss = 'mse',
+ metrics = c('mse')
+ )
> model %>% fit(
+ as.matrix(efw_train2), train2Label,
+ epochs=FLAGS$epochs,
+ batch_size=FLAGS$batch_size,
+ validation_data=list(as.matrix( .... [TRUNCATED]
Train on 3021 samples, validate on 334 samples
Epoch 1/30
500/3021 [===>..........................] - ETA: 1s - loss: 43.5178 - mse: 43.5178
3021/3021 [==============================] - 1s 261us/sample - loss: 27.9859 - mse: 27.9859 - val_loss: 3.4670 - val_mse: 3.4670
Epoch 2/30
500/3021 [===>..........................] - ETA: 0s - loss: 3.1240 - mse: 3.1240
3021/3021 [==============================] - 1s 190us/sample - loss: 3.9050 - mse: 3.9050 - val_loss: 3.3481 - val_mse: 3.3481
Epoch 3/30
500/3021 [===>..........................] - ETA: 0s - loss: 4.2364 - mse: 4.2364
3021/3021 [==============================] - 1s 166us/sample - loss: 2.0418 - mse: 2.0418 - val_loss: 2.1908 - val_mse: 2.1908
Epoch 4/30
500/3021 [===>..........................] - ETA: 0s - loss: 2.3995 - mse: 2.3995
3021/3021 [==============================] - 0s 151us/sample - loss: 2.2063 - mse: 2.2063 - val_loss: 0.3245 - val_mse: 0.3245
Epoch 5/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.7416 - mse: 0.7416
3021/3021 [==============================] - 0s 155us/sample - loss: 1.0438 - mse: 1.0438 - val_loss: 0.7301 - val_mse: 0.7301
Epoch 6/30
500/3021 [===>..........................] - ETA: 0s - loss: 1.2039 - mse: 1.2039
3021/3021 [==============================] - 0s 139us/sample - loss: 0.8784 - mse: 0.8784 - val_loss: 0.5625 - val_mse: 0.5625
Epoch 7/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.9010 - mse: 0.9010
3021/3021 [==============================] - 0s 152us/sample - loss: 0.8297 - mse: 0.8297 - val_loss: 0.3494 - val_mse: 0.3494
Epoch 8/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.7120 - mse: 0.7120
3021/3021 [==============================] - 1s 170us/sample - loss: 0.6784 - mse: 0.6784 - val_loss: 0.1633 - val_mse: 0.1633
Epoch 9/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.5265 - mse: 0.5265
3000/3021 [============================>.] - ETA: 0s - loss: 0.5517 - mse: 0.5517
3021/3021 [==============================] - 1s 206us/sample - loss: 0.5516 - mse: 0.5516 - val_loss: 0.1986 - val_mse: 0.1986
Epoch 10/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.5053 - mse: 0.5053
3021/3021 [==============================] - 0s 162us/sample - loss: 0.4775 - mse: 0.4775 - val_loss: 0.1955 - val_mse: 0.1955
Epoch 11/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.5343 - mse: 0.5343
3021/3021 [==============================] - 0s 157us/sample - loss: 0.4576 - mse: 0.4576 - val_loss: 0.1367 - val_mse: 0.1367
Epoch 12/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.4111 - mse: 0.4111
3000/3021 [============================>.] - ETA: 0s - loss: 0.4401 - mse: 0.4401
3021/3021 [==============================] - 0s 159us/sample - loss: 0.4399 - mse: 0.4399 - val_loss: 0.1096 - val_mse: 0.1096
Epoch 13/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.3701 - mse: 0.3701
3021/3021 [==============================] - 0s 139us/sample - loss: 0.3990 - mse: 0.3990 - val_loss: 0.1182 - val_mse: 0.1182
Epoch 14/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.3677 - mse: 0.3677
3021/3021 [==============================] - 0s 160us/sample - loss: 0.3837 - mse: 0.3837 - val_loss: 0.1407 - val_mse: 0.1407
Epoch 15/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.4100 - mse: 0.4100
3021/3021 [==============================] - 0s 141us/sample - loss: 0.3763 - mse: 0.3763 - val_loss: 0.0822 - val_mse: 0.0822
Epoch 16/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.3667 - mse: 0.3667
3021/3021 [==============================] - 0s 153us/sample - loss: 0.3444 - mse: 0.3444 - val_loss: 0.0989 - val_mse: 0.0989
Epoch 17/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.3228 - mse: 0.3228
3021/3021 [==============================] - 0s 151us/sample - loss: 0.3267 - mse: 0.3267 - val_loss: 0.0821 - val_mse: 0.0821
Epoch 18/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.3475 - mse: 0.3475
3021/3021 [==============================] - 0s 158us/sample - loss: 0.3371 - mse: 0.3371 - val_loss: 0.0861 - val_mse: 0.0861
Epoch 19/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.3247 - mse: 0.3247
3021/3021 [==============================] - 1s 169us/sample - loss: 0.3362 - mse: 0.3362 - val_loss: 0.0956 - val_mse: 0.0956
Epoch 20/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.3017 - mse: 0.3017
3021/3021 [==============================] - 0s 145us/sample - loss: 0.3146 - mse: 0.3146 - val_loss: 0.1154 - val_mse: 0.1154
Epoch 21/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.3123 - mse: 0.3123
3021/3021 [==============================] - 0s 156us/sample - loss: 0.3237 - mse: 0.3237 - val_loss: 0.1373 - val_mse: 0.1373
Epoch 22/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.3527 - mse: 0.3527
3021/3021 [==============================] - 1s 184us/sample - loss: 0.3401 - mse: 0.3401 - val_loss: 0.0878 - val_mse: 0.0878
Epoch 23/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.3001 - mse: 0.3001
3021/3021 [==============================] - 1s 189us/sample - loss: 0.3159 - mse: 0.3159 - val_loss: 0.1240 - val_mse: 0.1240
Epoch 24/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.3448 - mse: 0.3448
3000/3021 [============================>.] - ETA: 0s - loss: 0.3437 - mse: 0.3437
3021/3021 [==============================] - 1s 177us/sample - loss: 0.3447 - mse: 0.3447 - val_loss: 0.1012 - val_mse: 0.1012
Epoch 25/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.3093 - mse: 0.3093
3021/3021 [==============================] - 0s 153us/sample - loss: 0.3292 - mse: 0.3292 - val_loss: 0.1588 - val_mse: 0.1588
Epoch 26/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.3537 - mse: 0.3537
3021/3021 [==============================] - 1s 184us/sample - loss: 0.3086 - mse: 0.3086 - val_loss: 0.1153 - val_mse: 0.1153
Epoch 27/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.2941 - mse: 0.2941
3000/3021 [============================>.] - ETA: 0s - loss: 0.3146 - mse: 0.3146
3021/3021 [==============================] - 0s 157us/sample - loss: 0.3144 - mse: 0.3144 - val_loss: 0.1120 - val_mse: 0.1120
Epoch 28/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.2814 - mse: 0.2814
3021/3021 [==============================] - 0s 153us/sample - loss: 0.2953 - mse: 0.2953 - val_loss: 0.1117 - val_mse: 0.1117
Epoch 29/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.3090 - mse: 0.3090
3021/3021 [==============================] - 0s 148us/sample - loss: 0.2919 - mse: 0.2919 - val_loss: 0.0807 - val_mse: 0.0807
Epoch 30/30
500/3021 [===>..........................] - ETA: 0s - loss: 0.2526 - mse: 0.2526
3021/3021 [==============================] - 0s 154us/sample - loss: 0.2847 - mse: 0.2847 - val_loss: 0.0853 - val_mse: 0.0853Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-05-04T01-13-53Z
Training run 43/46 (flags = list(392, 128, 1e-04, 200, 30, "relu", "sigmoid", 0.1, 0.1))
Using run directory runs/2020-05-04T01-14-12Z
> FLAGS <- flags(
+ flag_numeric("nodes1", 128),
+ flag_numeric("nodes2", 128),
+ flag_numeric("batch_size", 100),
+ flag_string("activation1" .... [TRUNCATED]
> model = keras_model_sequential()
> model %>%
+ layer_dense(units=FLAGS$nodes1, activation=FLAGS$activation1, input_shape=dim(efw_train2)[2]) %>%
+ layer_dropout(FLAGS$dropout1) %> .... [TRUNCATED]
> model %>% compile(
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ loss = 'mse',
+ metrics = c('mse')
+ )
> model %>% fit(
+ as.matrix(efw_train2), train2Label,
+ epochs=FLAGS$epochs,
+ batch_size=FLAGS$batch_size,
+ validation_data=list(as.matrix( .... [TRUNCATED]
Train on 3021 samples, validate on 334 samples
Epoch 1/30
200/3021 [>.............................] - ETA: 3s - loss: 42.6610 - mse: 42.6610
2600/3021 [========================>.....] - ETA: 0s - loss: 40.3097 - mse: 40.3097
3021/3021 [==============================] - 1s 266us/sample - loss: 40.0585 - mse: 40.0585 - val_loss: 38.3395 - val_mse: 38.3395
Epoch 2/30
200/3021 [>.............................] - ETA: 0s - loss: 38.6118 - mse: 38.6118
2200/3021 [====================>.........] - ETA: 0s - loss: 37.2669 - mse: 37.2669
3021/3021 [==============================] - 0s 156us/sample - loss: 37.0335 - mse: 37.0335 - val_loss: 35.3968 - val_mse: 35.3968
Epoch 3/30
200/3021 [>.............................] - ETA: 0s - loss: 35.2259 - mse: 35.2259
2200/3021 [====================>.........] - ETA: 0s - loss: 34.5243 - mse: 34.5243
3021/3021 [==============================] - 0s 163us/sample - loss: 34.1815 - mse: 34.1815 - val_loss: 32.6365 - val_mse: 32.6365
Epoch 4/30
200/3021 [>.............................] - ETA: 0s - loss: 32.2926 - mse: 32.2926
2200/3021 [====================>.........] - ETA: 0s - loss: 32.0580 - mse: 32.0580
3021/3021 [==============================] - 0s 150us/sample - loss: 31.5160 - mse: 31.5160 - val_loss: 30.0401 - val_mse: 30.0401
Epoch 5/30
200/3021 [>.............................] - ETA: 0s - loss: 30.4960 - mse: 30.4960
2600/3021 [========================>.....] - ETA: 0s - loss: 29.1230 - mse: 29.1230
3021/3021 [==============================] - 0s 156us/sample - loss: 28.9811 - mse: 28.9811 - val_loss: 27.6132 - val_mse: 27.6132
Epoch 6/30
200/3021 [>.............................] - ETA: 0s - loss: 27.3664 - mse: 27.3664
2600/3021 [========================>.....] - ETA: 0s - loss: 26.7666 - mse: 26.7666
3021/3021 [==============================] - 0s 144us/sample - loss: 26.6206 - mse: 26.6206 - val_loss: 25.3446 - val_mse: 25.3446
Epoch 7/30
200/3021 [>.............................] - ETA: 0s - loss: 24.4453 - mse: 24.4453
2600/3021 [========================>.....] - ETA: 0s - loss: 24.5159 - mse: 24.5159
3021/3021 [==============================] - 1s 205us/sample - loss: 24.4380 - mse: 24.4380 - val_loss: 23.2248 - val_mse: 23.2248
Epoch 8/30
200/3021 [>.............................] - ETA: 0s - loss: 24.0951 - mse: 24.0951
2000/3021 [==================>...........] - ETA: 0s - loss: 22.7381 - mse: 22.7381
3021/3021 [==============================] - 0s 160us/sample - loss: 22.4124 - mse: 22.4124 - val_loss: 21.2531 - val_mse: 21.2531
Epoch 9/30
200/3021 [>.............................] - ETA: 0s - loss: 21.5870 - mse: 21.5870
2400/3021 [======================>.......] - ETA: 0s - loss: 20.6834 - mse: 20.6834
3021/3021 [==============================] - 0s 159us/sample - loss: 20.5163 - mse: 20.5163 - val_loss: 19.4387 - val_mse: 19.4387
Epoch 10/30
200/3021 [>.............................] - ETA: 0s - loss: 19.7006 - mse: 19.7006
2600/3021 [========================>.....] - ETA: 0s - loss: 18.8625 - mse: 18.8625
3021/3021 [==============================] - 0s 155us/sample - loss: 18.8088 - mse: 18.8088 - val_loss: 17.8166 - val_mse: 17.8166
Epoch 11/30
200/3021 [>.............................] - ETA: 0s - loss: 18.7523 - mse: 18.7523
2600/3021 [========================>.....] - ETA: 0s - loss: 17.4873 - mse: 17.4873
3021/3021 [==============================] - 1s 183us/sample - loss: 17.2503 - mse: 17.2503 - val_loss: 16.3601 - val_mse: 16.3601
Epoch 12/30
200/3021 [>.............................] - ETA: 0s - loss: 16.4283 - mse: 16.4283
2200/3021 [====================>.........] - ETA: 0s - loss: 15.8127 - mse: 15.8127
3021/3021 [==============================] - 1s 173us/sample - loss: 15.8847 - mse: 15.8847 - val_loss: 15.0631 - val_mse: 15.0631
Epoch 13/30
200/3021 [>.............................] - ETA: 0s - loss: 14.5900 - mse: 14.5900
2400/3021 [======================>.......] - ETA: 0s - loss: 14.7890 - mse: 14.7890
3021/3021 [==============================] - 0s 163us/sample - loss: 14.6400 - mse: 14.6400 - val_loss: 13.9067 - val_mse: 13.9067
Epoch 14/30
200/3021 [>.............................] - ETA: 0s - loss: 14.1395 - mse: 14.1395
2600/3021 [========================>.....] - ETA: 0s - loss: 13.7732 - mse: 13.7732
3021/3021 [==============================] - 0s 160us/sample - loss: 13.5749 - mse: 13.5749 - val_loss: 12.8857 - val_mse: 12.8857
Epoch 15/30
200/3021 [>.............................] - ETA: 0s - loss: 13.1911 - mse: 13.1911
2400/3021 [======================>.......] - ETA: 0s - loss: 12.6382 - mse: 12.6382
3021/3021 [==============================] - 0s 161us/sample - loss: 12.6122 - mse: 12.6122 - val_loss: 11.9727 - val_mse: 11.9727
Epoch 16/30
200/3021 [>.............................] - ETA: 0s - loss: 12.6498 - mse: 12.6498
2400/3021 [======================>.......] - ETA: 0s - loss: 11.6071 - mse: 11.6071
3021/3021 [==============================] - 1s 166us/sample - loss: 11.7181 - mse: 11.7181 - val_loss: 11.1688 - val_mse: 11.1688
Epoch 17/30
200/3021 [>.............................] - ETA: 0s - loss: 12.1216 - mse: 12.1216
2400/3021 [======================>.......] - ETA: 0s - loss: 11.0847 - mse: 11.0847
3021/3021 [==============================] - 1s 167us/sample - loss: 10.9927 - mse: 10.9927 - val_loss: 10.4530 - val_mse: 10.4530
Epoch 18/30
200/3021 [>.............................] - ETA: 0s - loss: 11.2645 - mse: 11.2645
2600/3021 [========================>.....] - ETA: 0s - loss: 10.4141 - mse: 10.4141
3021/3021 [==============================] - 0s 156us/sample - loss: 10.3339 - mse: 10.3339 - val_loss: 9.8139 - val_mse: 9.8139
Epoch 19/30
200/3021 [>.............................] - ETA: 0s - loss: 10.6812 - mse: 10.6812
1800/3021 [================>.............] - ETA: 0s - loss: 10.0523 - mse: 10.0523
3021/3021 [==============================] - 1s 182us/sample - loss: 9.7434 - mse: 9.7434 - val_loss: 9.2343 - val_mse: 9.2343
Epoch 20/30
200/3021 [>.............................] - ETA: 0s - loss: 9.7482 - mse: 9.7482
2400/3021 [======================>.......] - ETA: 0s - loss: 9.3268 - mse: 9.3268
3021/3021 [==============================] - 0s 163us/sample - loss: 9.1796 - mse: 9.1796 - val_loss: 8.7061 - val_mse: 8.7061
Epoch 21/30
200/3021 [>.............................] - ETA: 0s - loss: 9.4668 - mse: 9.4668
2600/3021 [========================>.....] - ETA: 0s - loss: 8.7201 - mse: 8.7201
3021/3021 [==============================] - 0s 160us/sample - loss: 8.6570 - mse: 8.6570 - val_loss: 8.2105 - val_mse: 8.2105
Epoch 22/30
200/3021 [>.............................] - ETA: 0s - loss: 7.8664 - mse: 7.8664
2800/3021 [==========================>...] - ETA: 0s - loss: 8.2211 - mse: 8.2211
3021/3021 [==============================] - 0s 151us/sample - loss: 8.2105 - mse: 8.2105 - val_loss: 7.7511 - val_mse: 7.7511
Epoch 23/30
200/3021 [>.............................] - ETA: 0s - loss: 7.7679 - mse: 7.7679
2800/3021 [==========================>...] - ETA: 0s - loss: 7.7717 - mse: 7.7717
3021/3021 [==============================] - 0s 155us/sample - loss: 7.7397 - mse: 7.7397 - val_loss: 7.3353 - val_mse: 7.3353
Epoch 24/30
200/3021 [>.............................] - ETA: 0s - loss: 7.6534 - mse: 7.6534
2600/3021 [========================>.....] - ETA: 0s - loss: 7.3857 - mse: 7.3857
3021/3021 [==============================] - 0s 164us/sample - loss: 7.3670 - mse: 7.3670 - val_loss: 6.9439 - val_mse: 6.9439
Epoch 25/30
200/3021 [>.............................] - ETA: 0s - loss: 6.3582 - mse: 6.3582
2200/3021 [====================>.........] - ETA: 0s - loss: 6.9867 - mse: 6.9867
3021/3021 [==============================] - 0s 165us/sample - loss: 7.0226 - mse: 7.0226 - val_loss: 6.5743 - val_mse: 6.5743
Epoch 26/30
200/3021 [>.............................] - ETA: 0s - loss: 6.9650 - mse: 6.9650
2400/3021 [======================>.......] - ETA: 0s - loss: 6.7030 - mse: 6.7030
3021/3021 [==============================] - 0s 163us/sample - loss: 6.6266 - mse: 6.6266 - val_loss: 6.2266 - val_mse: 6.2266
Epoch 27/30
200/3021 [>.............................] - ETA: 0s - loss: 6.1359 - mse: 6.1359
2600/3021 [========================>.....] - ETA: 0s - loss: 6.3237 - mse: 6.3237
3021/3021 [==============================] - 1s 168us/sample - loss: 6.3003 - mse: 6.3003 - val_loss: 5.9059 - val_mse: 5.9059
Epoch 28/30
200/3021 [>.............................] - ETA: 0s - loss: 6.0117 - mse: 6.0117
2400/3021 [======================>.......] - ETA: 0s - loss: 6.0503 - mse: 6.0503
3021/3021 [==============================] - 0s 160us/sample - loss: 6.0031 - mse: 6.0031 - val_loss: 5.5983 - val_mse: 5.5983
Epoch 29/30
200/3021 [>.............................] - ETA: 0s - loss: 5.6535 - mse: 5.6535
2000/3021 [==================>...........] - ETA: 0s - loss: 5.7018 - mse: 5.7018
3021/3021 [==============================] - 1s 204us/sample - loss: 5.6712 - mse: 5.6712 - val_loss: 5.3126 - val_mse: 5.3126
Epoch 30/30
200/3021 [>.............................] - ETA: 0s - loss: 6.1411 - mse: 6.1411
2400/3021 [======================>.......] - ETA: 0s - loss: 5.4091 - mse: 5.4091
3021/3021 [==============================] - 1s 181us/sample - loss: 5.3944 - mse: 5.3944 - val_loss: 5.0416 - val_mse: 5.0416Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-05-04T01-14-12Z
Training run 44/46 (flags = list(64, 64, 0.001, 100, 100, "relu", "relu", 0.05, 0.05))
Using run directory runs/2020-05-04T01-14-32Z
> FLAGS <- flags(
+ flag_numeric("nodes1", 128),
+ flag_numeric("nodes2", 128),
+ flag_numeric("batch_size", 100),
+ flag_string("activation1" .... [TRUNCATED]
> model = keras_model_sequential()
> model %>%
+ layer_dense(units=FLAGS$nodes1, activation=FLAGS$activation1, input_shape=dim(efw_train2)[2]) %>%
+ layer_dropout(FLAGS$dropout1) %> .... [TRUNCATED]
> model %>% compile(
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ loss = 'mse',
+ metrics = c('mse')
+ )
> model %>% fit(
+ as.matrix(efw_train2), train2Label,
+ epochs=FLAGS$epochs,
+ batch_size=FLAGS$batch_size,
+ validation_data=list(as.matrix( .... [TRUNCATED]
Train on 3021 samples, validate on 334 samples
Epoch 1/100
100/3021 [..............................] - ETA: 8s - loss: 43.6939 - mse: 43.6939
2100/3021 [===================>..........] - ETA: 0s - loss: 36.4162 - mse: 36.4162
3021/3021 [==============================] - 1s 274us/sample - loss: 33.5907 - mse: 33.5908 - val_loss: 25.0468 - val_mse: 25.0468
Epoch 2/100
100/3021 [..............................] - ETA: 0s - loss: 25.7273 - mse: 25.7273
2400/3021 [======================>.......] - ETA: 0s - loss: 20.0034 - mse: 20.0034
3021/3021 [==============================] - 0s 158us/sample - loss: 19.1437 - mse: 19.1437 - val_loss: 14.6080 - val_mse: 14.6081
Epoch 3/100
100/3021 [..............................] - ETA: 0s - loss: 14.6030 - mse: 14.6030
2000/3021 [==================>...........] - ETA: 0s - loss: 12.5217 - mse: 12.5217
3021/3021 [==============================] - 1s 191us/sample - loss: 11.7074 - mse: 11.7074 - val_loss: 9.3336 - val_mse: 9.3336
Epoch 4/100
100/3021 [..............................] - ETA: 0s - loss: 10.1031 - mse: 10.1031
2200/3021 [====================>.........] - ETA: 0s - loss: 8.2502 - mse: 8.2502
3021/3021 [==============================] - 1s 179us/sample - loss: 7.8293 - mse: 7.8293 - val_loss: 6.3551 - val_mse: 6.3551
Epoch 5/100
100/3021 [..............................] - ETA: 0s - loss: 5.7424 - mse: 5.7424
2400/3021 [======================>.......] - ETA: 0s - loss: 5.5247 - mse: 5.5247
3021/3021 [==============================] - 1s 180us/sample - loss: 5.3937 - mse: 5.3937 - val_loss: 4.3313 - val_mse: 4.3313
Epoch 6/100
100/3021 [..............................] - ETA: 0s - loss: 4.5867 - mse: 4.5867
1600/3021 [==============>...............] - ETA: 0s - loss: 4.0349 - mse: 4.0349
3021/3021 [==============================] - 1s 176us/sample - loss: 3.6763 - mse: 3.6763 - val_loss: 2.8622 - val_mse: 2.8622
Epoch 7/100
100/3021 [..............................] - ETA: 0s - loss: 2.7259 - mse: 2.7259
1800/3021 [================>.............] - ETA: 0s - loss: 2.6697 - mse: 2.6697
3021/3021 [==============================] - 1s 182us/sample - loss: 2.4166 - mse: 2.4166 - val_loss: 1.8594 - val_mse: 1.8594
Epoch 8/100
100/3021 [..............................] - ETA: 0s - loss: 2.0875 - mse: 2.0875
2100/3021 [===================>..........] - ETA: 0s - loss: 1.7478 - mse: 1.7478
3021/3021 [==============================] - 1s 183us/sample - loss: 1.6204 - mse: 1.6204 - val_loss: 1.2492 - val_mse: 1.2492
Epoch 9/100
100/3021 [..............................] - ETA: 0s - loss: 1.3766 - mse: 1.3766
1800/3021 [================>.............] - ETA: 0s - loss: 1.2246 - mse: 1.2246
3021/3021 [==============================] - 0s 151us/sample - loss: 1.1590 - mse: 1.1590 - val_loss: 0.8901 - val_mse: 0.8901
Epoch 10/100
100/3021 [..............................] - ETA: 0s - loss: 1.1382 - mse: 1.1382
2500/3021 [=======================>......] - ETA: 0s - loss: 0.8719 - mse: 0.8719
3021/3021 [==============================] - 0s 161us/sample - loss: 0.8645 - mse: 0.8645 - val_loss: 0.6771 - val_mse: 0.6771
Epoch 11/100
100/3021 [..............................] - ETA: 0s - loss: 0.6272 - mse: 0.6272
1800/3021 [================>.............] - ETA: 0s - loss: 0.7535 - mse: 0.7535
3021/3021 [==============================] - 1s 195us/sample - loss: 0.6955 - mse: 0.6955 - val_loss: 0.5489 - val_mse: 0.5489
Epoch 12/100
100/3021 [..............................] - ETA: 0s - loss: 0.7404 - mse: 0.7404
1800/3021 [================>.............] - ETA: 0s - loss: 0.6026 - mse: 0.6026
3021/3021 [==============================] - 1s 237us/sample - loss: 0.5744 - mse: 0.5744 - val_loss: 0.4668 - val_mse: 0.4668
Epoch 13/100
100/3021 [..............................] - ETA: 0s - loss: 0.5198 - mse: 0.5198
2000/3021 [==================>...........] - ETA: 0s - loss: 0.5329 - mse: 0.5329
3021/3021 [==============================] - 1s 193us/sample - loss: 0.5224 - mse: 0.5224 - val_loss: 0.4163 - val_mse: 0.4163
Epoch 14/100
100/3021 [..............................] - ETA: 0s - loss: 0.4364 - mse: 0.4364
1700/3021 [===============>..............] - ETA: 0s - loss: 0.4599 - mse: 0.4599
3021/3021 [==============================] - 1s 170us/sample - loss: 0.4669 - mse: 0.4669 - val_loss: 0.3657 - val_mse: 0.3657
Epoch 15/100
100/3021 [..............................] - ETA: 0s - loss: 0.4893 - mse: 0.4893
2400/3021 [======================>.......] - ETA: 0s - loss: 0.4227 - mse: 0.4227
3021/3021 [==============================] - 1s 167us/sample - loss: 0.4253 - mse: 0.4253 - val_loss: 0.3332 - val_mse: 0.3332
Epoch 16/100
100/3021 [..............................] - ETA: 0s - loss: 0.3193 - mse: 0.3193
2200/3021 [====================>.........] - ETA: 0s - loss: 0.3801 - mse: 0.3801
3021/3021 [==============================] - 1s 170us/sample - loss: 0.3813 - mse: 0.3813 - val_loss: 0.3114 - val_mse: 0.3114
Epoch 17/100
100/3021 [..............................] - ETA: 0s - loss: 0.3486 - mse: 0.3486
1600/3021 [==============>...............] - ETA: 0s - loss: 0.3632 - mse: 0.3632
3021/3021 [==============================] - 1s 187us/sample - loss: 0.3627 - mse: 0.3627 - val_loss: 0.2880 - val_mse: 0.2880
Epoch 18/100
100/3021 [..............................] - ETA: 0s - loss: 0.2473 - mse: 0.2473
1500/3021 [=============>................] - ETA: 0s - loss: 0.3566 - mse: 0.3566
3021/3021 [==============================] - 1s 191us/sample - loss: 0.3470 - mse: 0.3470 - val_loss: 0.2689 - val_mse: 0.2689
Epoch 19/100
100/3021 [..............................] - ETA: 0s - loss: 0.3182 - mse: 0.3182
1800/3021 [================>.............] - ETA: 0s - loss: 0.3335 - mse: 0.3335
3021/3021 [==============================] - 1s 189us/sample - loss: 0.3289 - mse: 0.3289 - val_loss: 0.2487 - val_mse: 0.2487
Epoch 20/100
100/3021 [..............................] - ETA: 0s - loss: 0.3234 - mse: 0.3234
2300/3021 [=====================>........] - ETA: 0s - loss: 0.3196 - mse: 0.3196
3021/3021 [==============================] - 1s 172us/sample - loss: 0.3052 - mse: 0.3052 - val_loss: 0.2330 - val_mse: 0.2330
Epoch 21/100
100/3021 [..............................] - ETA: 0s - loss: 0.3414 - mse: 0.3414
2200/3021 [====================>.........] - ETA: 0s - loss: 0.2929 - mse: 0.2929
3021/3021 [==============================] - 0s 160us/sample - loss: 0.2899 - mse: 0.2899 - val_loss: 0.2222 - val_mse: 0.2222
Epoch 22/100
100/3021 [..............................] - ETA: 0s - loss: 0.3788 - mse: 0.3788
2400/3021 [======================>.......] - ETA: 0s - loss: 0.2677 - mse: 0.2677
3021/3021 [==============================] - 0s 160us/sample - loss: 0.2666 - mse: 0.2666 - val_loss: 0.2084 - val_mse: 0.2084
Epoch 23/100
100/3021 [..............................] - ETA: 0s - loss: 0.2773 - mse: 0.2773
1200/3021 [==========>...................] - ETA: 0s - loss: 0.2541 - mse: 0.2541
3021/3021 [==============================] - 1s 166us/sample - loss: 0.2709 - mse: 0.2709 - val_loss: 0.1964 - val_mse: 0.1964
Epoch 24/100
100/3021 [..............................] - ETA: 0s - loss: 0.1796 - mse: 0.1796
1400/3021 [============>.................] - ETA: 0s - loss: 0.2477 - mse: 0.2477
3021/3021 [==============================] - 1s 174us/sample - loss: 0.2419 - mse: 0.2419 - val_loss: 0.1840 - val_mse: 0.1840
Epoch 25/100
100/3021 [..............................] - ETA: 0s - loss: 0.2118 - mse: 0.2118
2400/3021 [======================>.......] - ETA: 0s - loss: 0.2394 - mse: 0.2394
3021/3021 [==============================] - 0s 158us/sample - loss: 0.2387 - mse: 0.2387 - val_loss: 0.1781 - val_mse: 0.1781
Epoch 26/100
100/3021 [..............................] - ETA: 0s - loss: 0.2149 - mse: 0.2149
2100/3021 [===================>..........] - ETA: 0s - loss: 0.2364 - mse: 0.2364
3021/3021 [==============================] - 0s 153us/sample - loss: 0.2387 - mse: 0.2387 - val_loss: 0.1660 - val_mse: 0.1660
Epoch 27/100
100/3021 [..............................] - ETA: 0s - loss: 0.1733 - mse: 0.1733
2400/3021 [======================>.......] - ETA: 0s - loss: 0.2224 - mse: 0.2224
3021/3021 [==============================] - 0s 155us/sample - loss: 0.2221 - mse: 0.2221 - val_loss: 0.1613 - val_mse: 0.1613
Epoch 28/100
100/3021 [..............................] - ETA: 0s - loss: 0.2389 - mse: 0.2389
2400/3021 [======================>.......] - ETA: 0s - loss: 0.2135 - mse: 0.2135
3021/3021 [==============================] - 0s 152us/sample - loss: 0.2154 - mse: 0.2154 - val_loss: 0.1566 - val_mse: 0.1566
Epoch 29/100
100/3021 [..............................] - ETA: 0s - loss: 0.1714 - mse: 0.1714
1900/3021 [=================>............] - ETA: 0s - loss: 0.2074 - mse: 0.2074
3021/3021 [==============================] - 1s 189us/sample - loss: 0.2134 - mse: 0.2134 - val_loss: 0.1517 - val_mse: 0.1517
Epoch 30/100
100/3021 [..............................] - ETA: 0s - loss: 0.2057 - mse: 0.2057
1500/3021 [=============>................] - ETA: 0s - loss: 0.2141 - mse: 0.2141
2600/3021 [========================>.....] - ETA: 0s - loss: 0.2099 - mse: 0.2099
3021/3021 [==============================] - 1s 187us/sample - loss: 0.2070 - mse: 0.2070 - val_loss: 0.1418 - val_mse: 0.1418
Epoch 31/100
100/3021 [..............................] - ETA: 0s - loss: 0.1871 - mse: 0.1871
2000/3021 [==================>...........] - ETA: 0s - loss: 0.2033 - mse: 0.2033
3021/3021 [==============================] - 1s 212us/sample - loss: 0.1972 - mse: 0.1972 - val_loss: 0.1399 - val_mse: 0.1399
Epoch 32/100
100/3021 [..............................] - ETA: 0s - loss: 0.1793 - mse: 0.1793
2000/3021 [==================>...........] - ETA: 0s - loss: 0.2044 - mse: 0.2044
3021/3021 [==============================] - 1s 182us/sample - loss: 0.1992 - mse: 0.1992 - val_loss: 0.1336 - val_mse: 0.1336
Epoch 33/100
100/3021 [..............................] - ETA: 0s - loss: 0.2159 - mse: 0.2159
2000/3021 [==================>...........] - ETA: 0s - loss: 0.1944 - mse: 0.1944
3021/3021 [==============================] - 1s 195us/sample - loss: 0.1878 - mse: 0.1878 - val_loss: 0.1293 - val_mse: 0.1293
Epoch 34/100
100/3021 [..............................] - ETA: 0s - loss: 0.1687 - mse: 0.1687
2300/3021 [=====================>........] - ETA: 0s - loss: 0.1845 - mse: 0.1845
3021/3021 [==============================] - 0s 158us/sample - loss: 0.1863 - mse: 0.1863 - val_loss: 0.1277 - val_mse: 0.1277
Epoch 35/100
100/3021 [..............................] - ETA: 0s - loss: 0.1579 - mse: 0.1579
2500/3021 [=======================>......] - ETA: 0s - loss: 0.1780 - mse: 0.1780
3021/3021 [==============================] - 0s 157us/sample - loss: 0.1754 - mse: 0.1754 - val_loss: 0.1262 - val_mse: 0.1262
Epoch 36/100
100/3021 [..............................] - ETA: 0s - loss: 0.1621 - mse: 0.1621
1500/3021 [=============>................] - ETA: 0s - loss: 0.1753 - mse: 0.1753
3021/3021 [==============================] - 1s 176us/sample - loss: 0.1744 - mse: 0.1744 - val_loss: 0.1193 - val_mse: 0.1193
Epoch 37/100
100/3021 [..............................] - ETA: 0s - loss: 0.1632 - mse: 0.1632
2700/3021 [=========================>....] - ETA: 0s - loss: 0.1725 - mse: 0.1725
3021/3021 [==============================] - 0s 160us/sample - loss: 0.1719 - mse: 0.1719 - val_loss: 0.1197 - val_mse: 0.1197
Epoch 38/100
100/3021 [..............................] - ETA: 0s - loss: 0.1566 - mse: 0.1566
1600/3021 [==============>...............] - ETA: 0s - loss: 0.1697 - mse: 0.1697
3021/3021 [==============================] - 0s 161us/sample - loss: 0.1680 - mse: 0.1680 - val_loss: 0.1160 - val_mse: 0.1160
Epoch 39/100
100/3021 [..............................] - ETA: 0s - loss: 0.1741 - mse: 0.1741
2500/3021 [=======================>......] - ETA: 0s - loss: 0.1719 - mse: 0.1719
3021/3021 [==============================] - 0s 159us/sample - loss: 0.1744 - mse: 0.1744 - val_loss: 0.1105 - val_mse: 0.1105
Epoch 40/100
100/3021 [..............................] - ETA: 0s - loss: 0.1102 - mse: 0.1102
2100/3021 [===================>..........] - ETA: 0s - loss: 0.1687 - mse: 0.1687
3021/3021 [==============================] - 1s 175us/sample - loss: 0.1646 - mse: 0.1646 - val_loss: 0.1054 - val_mse: 0.1054
Epoch 41/100
100/3021 [..............................] - ETA: 0s - loss: 0.1530 - mse: 0.1530
1900/3021 [=================>............] - ETA: 0s - loss: 0.1613 - mse: 0.1613
3021/3021 [==============================] - 1s 168us/sample - loss: 0.1567 - mse: 0.1567 - val_loss: 0.1060 - val_mse: 0.1060
Epoch 42/100
100/3021 [..............................] - ETA: 0s - loss: 0.1748 - mse: 0.1748
1300/3021 [===========>..................] - ETA: 0s - loss: 0.1645 - mse: 0.1645
3021/3021 [==============================] - 0s 157us/sample - loss: 0.1612 - mse: 0.1612 - val_loss: 0.1008 - val_mse: 0.1008
Epoch 43/100
100/3021 [..............................] - ETA: 0s - loss: 0.1583 - mse: 0.1583
2000/3021 [==================>...........] - ETA: 0s - loss: 0.1567 - mse: 0.1567
3021/3021 [==============================] - 0s 164us/sample - loss: 0.1568 - mse: 0.1568 - val_loss: 0.0986 - val_mse: 0.0986
Epoch 44/100
100/3021 [..............................] - ETA: 0s - loss: 0.1703 - mse: 0.1703
1900/3021 [=================>............] - ETA: 0s - loss: 0.1529 - mse: 0.1529
3021/3021 [==============================] - 0s 152us/sample - loss: 0.1539 - mse: 0.1539 - val_loss: 0.0956 - val_mse: 0.0956
Epoch 45/100
100/3021 [..............................] - ETA: 0s - loss: 0.1472 - mse: 0.1472
2800/3021 [==========================>...] - ETA: 0s - loss: 0.1549 - mse: 0.1549
3021/3021 [==============================] - 0s 154us/sample - loss: 0.1531 - mse: 0.1531 - val_loss: 0.0938 - val_mse: 0.0938
Epoch 46/100
100/3021 [..............................] - ETA: 0s - loss: 0.1948 - mse: 0.1948
1100/3021 [=========>....................] - ETA: 0s - loss: 0.1591 - mse: 0.1591
2900/3021 [===========================>..] - ETA: 0s - loss: 0.1514 - mse: 0.1514
3021/3021 [==============================] - 0s 161us/sample - loss: 0.1517 - mse: 0.1517 - val_loss: 0.0965 - val_mse: 0.0965
Epoch 47/100
100/3021 [..............................] - ETA: 0s - loss: 0.1487 - mse: 0.1487
2700/3021 [=========================>....] - ETA: 0s - loss: 0.1492 - mse: 0.1492
3021/3021 [==============================] - 0s 153us/sample - loss: 0.1491 - mse: 0.1491 - val_loss: 0.0940 - val_mse: 0.0940
Epoch 48/100
100/3021 [..............................] - ETA: 0s - loss: 0.1752 - mse: 0.1752
2700/3021 [=========================>....] - ETA: 0s - loss: 0.1444 - mse: 0.1444
3021/3021 [==============================] - 0s 150us/sample - loss: 0.1435 - mse: 0.1435 - val_loss: 0.0902 - val_mse: 0.0902
Epoch 49/100
100/3021 [..............................] - ETA: 0s - loss: 0.1556 - mse: 0.1556
2400/3021 [======================>.......] - ETA: 0s - loss: 0.1602 - mse: 0.1602
3021/3021 [==============================] - 1s 173us/sample - loss: 0.1551 - mse: 0.1551 - val_loss: 0.0883 - val_mse: 0.0883
Epoch 50/100
100/3021 [..............................] - ETA: 0s - loss: 0.1365 - mse: 0.1365
1800/3021 [================>.............] - ETA: 0s - loss: 0.1406 - mse: 0.1406
3021/3021 [==============================] - 1s 173us/sample - loss: 0.1405 - mse: 0.1405 - val_loss: 0.0879 - val_mse: 0.0879
Epoch 51/100
100/3021 [..............................] - ETA: 0s - loss: 0.1375 - mse: 0.1375
2000/3021 [==================>...........] - ETA: 0s - loss: 0.1346 - mse: 0.1346
3021/3021 [==============================] - 1s 167us/sample - loss: 0.1382 - mse: 0.1382 - val_loss: 0.0871 - val_mse: 0.0871
Epoch 52/100
100/3021 [..............................] - ETA: 0s - loss: 0.1237 - mse: 0.1237
1200/3021 [==========>...................] - ETA: 0s - loss: 0.1292 - mse: 0.1292
3021/3021 [==============================] - 0s 158us/sample - loss: 0.1354 - mse: 0.1354 - val_loss: 0.0870 - val_mse: 0.0870
Epoch 53/100
100/3021 [..............................] - ETA: 0s - loss: 0.0974 - mse: 0.0974
2500/3021 [=======================>......] - ETA: 0s - loss: 0.1413 - mse: 0.1413
3021/3021 [==============================] - 0s 153us/sample - loss: 0.1412 - mse: 0.1412 - val_loss: 0.0863 - val_mse: 0.0863
Epoch 54/100
100/3021 [..............................] - ETA: 0s - loss: 0.1299 - mse: 0.1299
2200/3021 [====================>.........] - ETA: 0s - loss: 0.1375 - mse: 0.1375
3021/3021 [==============================] - 0s 164us/sample - loss: 0.1372 - mse: 0.1372 - val_loss: 0.0828 - val_mse: 0.0828
Epoch 55/100
100/3021 [..............................] - ETA: 0s - loss: 0.1301 - mse: 0.1301
2600/3021 [========================>.....] - ETA: 0s - loss: 0.1349 - mse: 0.1349
3021/3021 [==============================] - 0s 152us/sample - loss: 0.1354 - mse: 0.1354 - val_loss: 0.0780 - val_mse: 0.0780
Epoch 56/100
100/3021 [..............................] - ETA: 0s - loss: 0.1220 - mse: 0.1220
2000/3021 [==================>...........] - ETA: 0s - loss: 0.1321 - mse: 0.1321
3021/3021 [==============================] - 1s 167us/sample - loss: 0.1289 - mse: 0.1289 - val_loss: 0.0782 - val_mse: 0.0782
Epoch 57/100
100/3021 [..............................] - ETA: 0s - loss: 0.1286 - mse: 0.1286
1700/3021 [===============>..............] - ETA: 0s - loss: 0.1355 - mse: 0.1355
3021/3021 [==============================] - 0s 165us/sample - loss: 0.1387 - mse: 0.1387 - val_loss: 0.0767 - val_mse: 0.0767
Epoch 58/100
100/3021 [..............................] - ETA: 0s - loss: 0.1429 - mse: 0.1429
2700/3021 [=========================>....] - ETA: 0s - loss: 0.1302 - mse: 0.1302
3021/3021 [==============================] - 0s 161us/sample - loss: 0.1301 - mse: 0.1301 - val_loss: 0.0774 - val_mse: 0.0774
Epoch 59/100
100/3021 [..............................] - ETA: 0s - loss: 0.2001 - mse: 0.2001
1900/3021 [=================>............] - ETA: 0s - loss: 0.1290 - mse: 0.1290
3021/3021 [==============================] - 1s 178us/sample - loss: 0.1292 - mse: 0.1292 - val_loss: 0.0752 - val_mse: 0.0752
Epoch 60/100
100/3021 [..............................] - ETA: 0s - loss: 0.1229 - mse: 0.1229
2300/3021 [=====================>........] - ETA: 0s - loss: 0.1270 - mse: 0.1270
3021/3021 [==============================] - 0s 159us/sample - loss: 0.1254 - mse: 0.1254 - val_loss: 0.0770 - val_mse: 0.0770
Epoch 61/100
100/3021 [..............................] - ETA: 0s - loss: 0.1168 - mse: 0.1168
1600/3021 [==============>...............] - ETA: 0s - loss: 0.1234 - mse: 0.1234
3021/3021 [==============================] - 0s 159us/sample - loss: 0.1195 - mse: 0.1195 - val_loss: 0.0750 - val_mse: 0.0750
Epoch 62/100
100/3021 [..............................] - ETA: 0s - loss: 0.1647 - mse: 0.1647
2600/3021 [========================>.....] - ETA: 0s - loss: 0.1295 - mse: 0.1295
3021/3021 [==============================] - 0s 143us/sample - loss: 0.1309 - mse: 0.1309 - val_loss: 0.0714 - val_mse: 0.0714
Epoch 63/100
100/3021 [..............................] - ETA: 0s - loss: 0.1219 - mse: 0.1219
2200/3021 [====================>.........] - ETA: 0s - loss: 0.1321 - mse: 0.1321
3021/3021 [==============================] - 0s 154us/sample - loss: 0.1282 - mse: 0.1282 - val_loss: 0.0718 - val_mse: 0.0718
Epoch 64/100
100/3021 [..............................] - ETA: 0s - loss: 0.1077 - mse: 0.1077
2300/3021 [=====================>........] - ETA: 0s - loss: 0.1259 - mse: 0.1259
3021/3021 [==============================] - 0s 150us/sample - loss: 0.1261 - mse: 0.1261 - val_loss: 0.0752 - val_mse: 0.0752
Epoch 65/100
100/3021 [..............................] - ETA: 0s - loss: 0.1470 - mse: 0.1470
2400/3021 [======================>.......] - ETA: 0s - loss: 0.1286 - mse: 0.1286
3021/3021 [==============================] - 0s 158us/sample - loss: 0.1283 - mse: 0.1283 - val_loss: 0.0718 - val_mse: 0.0718
Epoch 66/100
100/3021 [..............................] - ETA: 0s - loss: 0.1210 - mse: 0.1210
2100/3021 [===================>..........] - ETA: 0s - loss: 0.1214 - mse: 0.1214
3021/3021 [==============================] - 0s 152us/sample - loss: 0.1285 - mse: 0.1285 - val_loss: 0.0703 - val_mse: 0.0703
Epoch 67/100
100/3021 [..............................] - ETA: 0s - loss: 0.1294 - mse: 0.1294
1400/3021 [============>.................] - ETA: 0s - loss: 0.1188 - mse: 0.1188
3021/3021 [==============================] - 0s 150us/sample - loss: 0.1211 - mse: 0.1211 - val_loss: 0.0670 - val_mse: 0.0670
Epoch 68/100
100/3021 [..............................] - ETA: 0s - loss: 0.1458 - mse: 0.1458
2000/3021 [==================>...........] - ETA: 0s - loss: 0.1233 - mse: 0.1233
3021/3021 [==============================] - 1s 175us/sample - loss: 0.1195 - mse: 0.1195 - val_loss: 0.0713 - val_mse: 0.0713
Epoch 69/100
100/3021 [..............................] - ETA: 0s - loss: 0.1199 - mse: 0.1199
2100/3021 [===================>..........] - ETA: 0s - loss: 0.1226 - mse: 0.1226
3021/3021 [==============================] - 1s 167us/sample - loss: 0.1199 - mse: 0.1199 - val_loss: 0.0670 - val_mse: 0.0670
Epoch 70/100
100/3021 [..............................] - ETA: 0s - loss: 0.1040 - mse: 0.1040
2200/3021 [====================>.........] - ETA: 0s - loss: 0.1214 - mse: 0.1214
3021/3021 [==============================] - 1s 166us/sample - loss: 0.1243 - mse: 0.1243 - val_loss: 0.0641 - val_mse: 0.0641
Epoch 71/100
100/3021 [..............................] - ETA: 0s - loss: 0.1532 - mse: 0.1532
1900/3021 [=================>............] - ETA: 0s - loss: 0.1204 - mse: 0.1204
3021/3021 [==============================] - 1s 170us/sample - loss: 0.1238 - mse: 0.1238 - val_loss: 0.0673 - val_mse: 0.0673
Epoch 72/100
100/3021 [..............................] - ETA: 0s - loss: 0.0927 - mse: 0.0927
1700/3021 [===============>..............] - ETA: 0s - loss: 0.1173 - mse: 0.1173
3021/3021 [==============================] - 1s 196us/sample - loss: 0.1255 - mse: 0.1255 - val_loss: 0.0595 - val_mse: 0.0595
Epoch 73/100
100/3021 [..............................] - ETA: 0s - loss: 0.1321 - mse: 0.1321
2000/3021 [==================>...........] - ETA: 0s - loss: 0.1199 - mse: 0.1199
3021/3021 [==============================] - 1s 169us/sample - loss: 0.1174 - mse: 0.1174 - val_loss: 0.0628 - val_mse: 0.0628
Epoch 74/100
100/3021 [..............................] - ETA: 0s - loss: 0.1144 - mse: 0.1144
1800/3021 [================>.............] - ETA: 0s - loss: 0.1156 - mse: 0.1156
3021/3021 [==============================] - 0s 162us/sample - loss: 0.1204 - mse: 0.1204 - val_loss: 0.0595 - val_mse: 0.0595
Epoch 75/100
100/3021 [..............................] - ETA: 0s - loss: 0.1264 - mse: 0.1264
2200/3021 [====================>.........] - ETA: 0s - loss: 0.1153 - mse: 0.1153
3021/3021 [==============================] - 0s 163us/sample - loss: 0.1147 - mse: 0.1147 - val_loss: 0.0609 - val_mse: 0.0609
Epoch 76/100
100/3021 [..............................] - ETA: 0s - loss: 0.1182 - mse: 0.1182
1500/3021 [=============>................] - ETA: 0s - loss: 0.1129 - mse: 0.1129
3021/3021 [==============================] - 0s 151us/sample - loss: 0.1172 - mse: 0.1172 - val_loss: 0.0548 - val_mse: 0.0548
Epoch 77/100
100/3021 [..............................] - ETA: 0s - loss: 0.1242 - mse: 0.1242
2400/3021 [======================>.......] - ETA: 0s - loss: 0.1149 - mse: 0.1149
3021/3021 [==============================] - 0s 157us/sample - loss: 0.1151 - mse: 0.1151 - val_loss: 0.0594 - val_mse: 0.0594
Epoch 78/100
100/3021 [..............................] - ETA: 0s - loss: 0.1259 - mse: 0.1259
1600/3021 [==============>...............] - ETA: 0s - loss: 0.1115 - mse: 0.1115
3021/3021 [==============================] - 0s 159us/sample - loss: 0.1131 - mse: 0.1131 - val_loss: 0.0609 - val_mse: 0.0609
Epoch 79/100
100/3021 [..............................] - ETA: 0s - loss: 0.1419 - mse: 0.1419
1500/3021 [=============>................] - ETA: 0s - loss: 0.1130 - mse: 0.1130
3021/3021 [==============================] - 0s 161us/sample - loss: 0.1160 - mse: 0.1160 - val_loss: 0.0591 - val_mse: 0.0591
Epoch 80/100
100/3021 [..............................] - ETA: 0s - loss: 0.1241 - mse: 0.1241
1800/3021 [================>.............] - ETA: 0s - loss: 0.1162 - mse: 0.1162
3021/3021 [==============================] - 1s 169us/sample - loss: 0.1166 - mse: 0.1166 - val_loss: 0.0585 - val_mse: 0.0585
Epoch 81/100
100/3021 [..............................] - ETA: 0s - loss: 0.1291 - mse: 0.1291
1700/3021 [===============>..............] - ETA: 0s - loss: 0.1150 - mse: 0.1150
3021/3021 [==============================] - 1s 184us/sample - loss: 0.1132 - mse: 0.1132 - val_loss: 0.0594 - val_mse: 0.0594
Epoch 82/100
100/3021 [..............................] - ETA: 0s - loss: 0.0967 - mse: 0.0967
2000/3021 [==================>...........] - ETA: 0s - loss: 0.1117 - mse: 0.1117
3021/3021 [==============================] - 0s 161us/sample - loss: 0.1098 - mse: 0.1098 - val_loss: 0.0584 - val_mse: 0.0584
Epoch 83/100
100/3021 [..............................] - ETA: 0s - loss: 0.1199 - mse: 0.1199
1200/3021 [==========>...................] - ETA: 0s - loss: 0.1184 - mse: 0.1184
3021/3021 [==============================] - 1s 174us/sample - loss: 0.1133 - mse: 0.1133 - val_loss: 0.0580 - val_mse: 0.0580
Epoch 84/100
100/3021 [..............................] - ETA: 0s - loss: 0.1208 - mse: 0.1208
1600/3021 [==============>...............] - ETA: 0s - loss: 0.1155 - mse: 0.1155
3021/3021 [==============================] - 1s 175us/sample - loss: 0.1106 - mse: 0.1106 - val_loss: 0.0550 - val_mse: 0.0550
Epoch 85/100
100/3021 [..............................] - ETA: 0s - loss: 0.1203 - mse: 0.1203
2100/3021 [===================>..........] - ETA: 0s - loss: 0.1042 - mse: 0.1042
3021/3021 [==============================] - 1s 170us/sample - loss: 0.1067 - mse: 0.1067 - val_loss: 0.0571 - val_mse: 0.0571
Epoch 86/100
100/3021 [..............................] - ETA: 0s - loss: 0.1069 - mse: 0.1069
2600/3021 [========================>.....] - ETA: 0s - loss: 0.1097 - mse: 0.1097
3021/3021 [==============================] - 0s 164us/sample - loss: 0.1103 - mse: 0.1103 - val_loss: 0.0579 - val_mse: 0.0579
Epoch 87/100
100/3021 [..............................] - ETA: 0s - loss: 0.1095 - mse: 0.1095
1300/3021 [===========>..................] - ETA: 0s - loss: 0.1079 - mse: 0.1079
3021/3021 [==============================] - 0s 158us/sample - loss: 0.1094 - mse: 0.1094 - val_loss: 0.0563 - val_mse: 0.0563
Epoch 88/100
100/3021 [..............................] - ETA: 0s - loss: 0.0832 - mse: 0.0832
2400/3021 [======================>.......] - ETA: 0s - loss: 0.1137 - mse: 0.1137
3021/3021 [==============================] - 0s 149us/sample - loss: 0.1136 - mse: 0.1136 - val_loss: 0.0544 - val_mse: 0.0544
Epoch 89/100
100/3021 [..............................] - ETA: 0s - loss: 0.1222 - mse: 0.1222
2800/3021 [==========================>...] - ETA: 0s - loss: 0.1118 - mse: 0.1118
3021/3021 [==============================] - 0s 150us/sample - loss: 0.1104 - mse: 0.1104 - val_loss: 0.0536 - val_mse: 0.0536
Epoch 90/100
100/3021 [..............................] - ETA: 0s - loss: 0.0757 - mse: 0.0757
2800/3021 [==========================>...] - ETA: 0s - loss: 0.1064 - mse: 0.1064
3021/3021 [==============================] - 0s 160us/sample - loss: 0.1058 - mse: 0.1058 - val_loss: 0.0510 - val_mse: 0.0510
Epoch 91/100
100/3021 [..............................] - ETA: 0s - loss: 0.1098 - mse: 0.1098
2200/3021 [====================>.........] - ETA: 0s - loss: 0.1164 - mse: 0.1164
3021/3021 [==============================] - 1s 168us/sample - loss: 0.1139 - mse: 0.1139 - val_loss: 0.0516 - val_mse: 0.0516
Epoch 92/100
100/3021 [..............................] - ETA: 0s - loss: 0.1405 - mse: 0.1405
2400/3021 [======================>.......] - ETA: 0s - loss: 0.1059 - mse: 0.1059
3021/3021 [==============================] - 0s 153us/sample - loss: 0.1079 - mse: 0.1079 - val_loss: 0.0463 - val_mse: 0.0463
Epoch 93/100
100/3021 [..............................] - ETA: 0s - loss: 0.1082 - mse: 0.1082
2500/3021 [=======================>......] - ETA: 0s - loss: 0.1079 - mse: 0.1079
3021/3021 [==============================] - 0s 148us/sample - loss: 0.1067 - mse: 0.1067 - val_loss: 0.0523 - val_mse: 0.0523
Epoch 94/100
100/3021 [..............................] - ETA: 0s - loss: 0.0847 - mse: 0.0847
2200/3021 [====================>.........] - ETA: 0s - loss: 0.1088 - mse: 0.1088
3021/3021 [==============================] - 0s 155us/sample - loss: 0.1112 - mse: 0.1112 - val_loss: 0.0519 - val_mse: 0.0519
Epoch 95/100
100/3021 [..............................] - ETA: 0s - loss: 0.0818 - mse: 0.0818
1200/3021 [==========>...................] - ETA: 0s - loss: 0.1066 - mse: 0.1066
3021/3021 [==============================] - 0s 156us/sample - loss: 0.1027 - mse: 0.1027 - val_loss: 0.0474 - val_mse: 0.0474
Epoch 96/100
100/3021 [..............................] - ETA: 0s - loss: 0.0934 - mse: 0.0934
2300/3021 [=====================>........] - ETA: 0s - loss: 0.1042 - mse: 0.1042
3021/3021 [==============================] - 0s 157us/sample - loss: 0.1076 - mse: 0.1076 - val_loss: 0.0516 - val_mse: 0.0516
Epoch 97/100
100/3021 [..............................] - ETA: 0s - loss: 0.0896 - mse: 0.0896
1500/3021 [=============>................] - ETA: 0s - loss: 0.0992 - mse: 0.0992
3021/3021 [==============================] - 0s 154us/sample - loss: 0.1029 - mse: 0.1029 - val_loss: 0.0487 - val_mse: 0.0487
Epoch 98/100
100/3021 [..............................] - ETA: 0s - loss: 0.0834 - mse: 0.0834
2800/3021 [==========================>...] - ETA: 0s - loss: 0.0991 - mse: 0.0991
3021/3021 [==============================] - 0s 150us/sample - loss: 0.0985 - mse: 0.0985 - val_loss: 0.0492 - val_mse: 0.0492
Epoch 99/100
100/3021 [..............................] - ETA: 0s - loss: 0.1066 - mse: 0.1066
2600/3021 [========================>.....] - ETA: 0s - loss: 0.1007 - mse: 0.1007
3021/3021 [==============================] - 0s 150us/sample - loss: 0.1000 - mse: 0.1000 - val_loss: 0.0501 - val_mse: 0.0501
Epoch 100/100
100/3021 [..............................] - ETA: 0s - loss: 0.0755 - mse: 0.0755
2000/3021 [==================>...........] - ETA: 0s - loss: 0.1009 - mse: 0.1009
3021/3021 [==============================] - 0s 159us/sample - loss: 0.0994 - mse: 0.0994 - val_loss: 0.0473 - val_mse: 0.0473Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-05-04T01-14-32Z
Training run 45/46 (flags = list(128, 392, 0.05, 100, 100, "relu", "sigmoid", 0.2, 0.1))
Using run directory runs/2020-05-04T01-15-27Z
> FLAGS <- flags(
+ flag_numeric("nodes1", 128),
+ flag_numeric("nodes2", 128),
+ flag_numeric("batch_size", 100),
+ flag_string("activation1" .... [TRUNCATED]
> model = keras_model_sequential()
> model %>%
+ layer_dense(units=FLAGS$nodes1, activation=FLAGS$activation1, input_shape=dim(efw_train2)[2]) %>%
+ layer_dropout(FLAGS$dropout1) %> .... [TRUNCATED]
> model %>% compile(
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ loss = 'mse',
+ metrics = c('mse')
+ )
> model %>% fit(
+ as.matrix(efw_train2), train2Label,
+ epochs=FLAGS$epochs,
+ batch_size=FLAGS$batch_size,
+ validation_data=list(as.matrix( .... [TRUNCATED]
Train on 3021 samples, validate on 334 samples
Epoch 1/100
100/3021 [..............................] - ETA: 7s - loss: 40.2155 - mse: 40.2155
2000/3021 [==================>...........] - ETA: 0s - loss: 8.1533 - mse: 8.1533
3021/3021 [==============================] - 1s 282us/sample - loss: 5.9486 - mse: 5.9486 - val_loss: 0.9912 - val_mse: 0.9912
Epoch 2/100
100/3021 [..............................] - ETA: 0s - loss: 1.1665 - mse: 1.1665
1500/3021 [=============>................] - ETA: 0s - loss: 0.9889 - mse: 0.9889
3021/3021 [==============================] - 1s 194us/sample - loss: 1.0059 - mse: 1.0059 - val_loss: 0.4693 - val_mse: 0.4693
Epoch 3/100
100/3021 [..............................] - ETA: 0s - loss: 0.5548 - mse: 0.5548
1400/3021 [============>.................] - ETA: 0s - loss: 0.5591 - mse: 0.5591
3000/3021 [============================>.] - ETA: 0s - loss: 0.4866 - mse: 0.4866
3021/3021 [==============================] - 1s 190us/sample - loss: 0.4859 - mse: 0.4859 - val_loss: 0.3261 - val_mse: 0.3261
Epoch 4/100
100/3021 [..............................] - ETA: 0s - loss: 0.4738 - mse: 0.4738
1300/3021 [===========>..................] - ETA: 0s - loss: 0.4095 - mse: 0.4095
3021/3021 [==============================] - 0s 160us/sample - loss: 0.4076 - mse: 0.4076 - val_loss: 0.3006 - val_mse: 0.3006
Epoch 5/100
100/3021 [..............................] - ETA: 0s - loss: 0.4702 - mse: 0.4702
2000/3021 [==================>...........] - ETA: 0s - loss: 0.3634 - mse: 0.3634
3021/3021 [==============================] - 1s 167us/sample - loss: 0.3457 - mse: 0.3457 - val_loss: 0.3025 - val_mse: 0.3025
Epoch 6/100
100/3021 [..............................] - ETA: 0s - loss: 0.3448 - mse: 0.3448
1700/3021 [===============>..............] - ETA: 0s - loss: 0.4972 - mse: 0.4972
3021/3021 [==============================] - 1s 169us/sample - loss: 0.4651 - mse: 0.4651 - val_loss: 0.2580 - val_mse: 0.2580
Epoch 7/100
100/3021 [..............................] - ETA: 0s - loss: 0.3830 - mse: 0.3830
2000/3021 [==================>...........] - ETA: 0s - loss: 0.3358 - mse: 0.3358
3021/3021 [==============================] - 0s 162us/sample - loss: 0.3098 - mse: 0.3098 - val_loss: 0.1491 - val_mse: 0.1491
Epoch 8/100
100/3021 [..............................] - ETA: 0s - loss: 0.2202 - mse: 0.2202
1500/3021 [=============>................] - ETA: 0s - loss: 0.2774 - mse: 0.2774
3021/3021 [==============================] - 0s 152us/sample - loss: 0.2588 - mse: 0.2588 - val_loss: 0.1432 - val_mse: 0.1432
Epoch 9/100
100/3021 [..............................] - ETA: 0s - loss: 0.1629 - mse: 0.1629
1700/3021 [===============>..............] - ETA: 0s - loss: 0.2396 - mse: 0.2396
3021/3021 [==============================] - 0s 165us/sample - loss: 0.2416 - mse: 0.2416 - val_loss: 0.1324 - val_mse: 0.1324
Epoch 10/100
100/3021 [..............................] - ETA: 0s - loss: 0.2533 - mse: 0.2533
2200/3021 [====================>.........] - ETA: 0s - loss: 0.2848 - mse: 0.2848
3021/3021 [==============================] - 0s 160us/sample - loss: 0.2751 - mse: 0.2751 - val_loss: 0.2263 - val_mse: 0.2263
Epoch 11/100
100/3021 [..............................] - ETA: 0s - loss: 0.2838 - mse: 0.2838
2100/3021 [===================>..........] - ETA: 0s - loss: 0.2645 - mse: 0.2645
3021/3021 [==============================] - 0s 164us/sample - loss: 0.2558 - mse: 0.2558 - val_loss: 0.1185 - val_mse: 0.1185
Epoch 12/100
100/3021 [..............................] - ETA: 0s - loss: 0.2560 - mse: 0.2560
1700/3021 [===============>..............] - ETA: 0s - loss: 0.2934 - mse: 0.2934
3021/3021 [==============================] - 1s 181us/sample - loss: 0.2682 - mse: 0.2682 - val_loss: 0.1037 - val_mse: 0.1037
Epoch 13/100
100/3021 [..............................] - ETA: 0s - loss: 0.1756 - mse: 0.1756
1500/3021 [=============>................] - ETA: 0s - loss: 0.3362 - mse: 0.3362
3021/3021 [==============================] - 1s 185us/sample - loss: 0.2980 - mse: 0.2980 - val_loss: 0.1128 - val_mse: 0.1128
Epoch 14/100
100/3021 [..............................] - ETA: 0s - loss: 0.1814 - mse: 0.1814
1800/3021 [================>.............] - ETA: 0s - loss: 0.2475 - mse: 0.2475
3021/3021 [==============================] - 0s 163us/sample - loss: 0.2616 - mse: 0.2616 - val_loss: 0.1802 - val_mse: 0.1802
Epoch 15/100
100/3021 [..............................] - ETA: 0s - loss: 0.1848 - mse: 0.1848
2100/3021 [===================>..........] - ETA: 0s - loss: 0.2435 - mse: 0.2435
3021/3021 [==============================] - 0s 154us/sample - loss: 0.2249 - mse: 0.2249 - val_loss: 0.1079 - val_mse: 0.1079
Epoch 16/100
100/3021 [..............................] - ETA: 0s - loss: 0.1690 - mse: 0.1690
2100/3021 [===================>..........] - ETA: 0s - loss: 0.1935 - mse: 0.1935
3021/3021 [==============================] - 0s 163us/sample - loss: 0.1936 - mse: 0.1936 - val_loss: 0.0963 - val_mse: 0.0963
Epoch 17/100
100/3021 [..............................] - ETA: 0s - loss: 0.1435 - mse: 0.1435
1900/3021 [=================>............] - ETA: 0s - loss: 0.1726 - mse: 0.1726
3021/3021 [==============================] - 1s 184us/sample - loss: 0.1644 - mse: 0.1644 - val_loss: 0.1470 - val_mse: 0.1470
Epoch 18/100
100/3021 [..............................] - ETA: 0s - loss: 0.2002 - mse: 0.2002
2000/3021 [==================>...........] - ETA: 0s - loss: 0.1771 - mse: 0.1771
3021/3021 [==============================] - 0s 157us/sample - loss: 0.1882 - mse: 0.1882 - val_loss: 0.3580 - val_mse: 0.3580
Epoch 19/100
100/3021 [..............................] - ETA: 0s - loss: 0.2779 - mse: 0.2779
1800/3021 [================>.............] - ETA: 0s - loss: 0.2985 - mse: 0.2985
3021/3021 [==============================] - 1s 171us/sample - loss: 0.2566 - mse: 0.2566 - val_loss: 0.2559 - val_mse: 0.2559
Epoch 20/100
100/3021 [..............................] - ETA: 0s - loss: 0.2339 - mse: 0.2339
1500/3021 [=============>................] - ETA: 0s - loss: 0.1941 - mse: 0.1941
2900/3021 [===========================>..] - ETA: 0s - loss: 0.2039 - mse: 0.2039
3021/3021 [==============================] - 1s 178us/sample - loss: 0.2057 - mse: 0.2057 - val_loss: 0.1308 - val_mse: 0.1308
Epoch 21/100
100/3021 [..............................] - ETA: 0s - loss: 0.1522 - mse: 0.1522
2000/3021 [==================>...........] - ETA: 0s - loss: 0.1390 - mse: 0.1390
3021/3021 [==============================] - 0s 160us/sample - loss: 0.1336 - mse: 0.1336 - val_loss: 0.0630 - val_mse: 0.0630
Epoch 22/100
100/3021 [..............................] - ETA: 0s - loss: 0.1063 - mse: 0.1063
2300/3021 [=====================>........] - ETA: 0s - loss: 0.1207 - mse: 0.1207
3021/3021 [==============================] - 1s 201us/sample - loss: 0.1199 - mse: 0.1199 - val_loss: 0.1288 - val_mse: 0.1288
Epoch 23/100
100/3021 [..............................] - ETA: 0s - loss: 0.1722 - mse: 0.1722
1600/3021 [==============>...............] - ETA: 0s - loss: 0.1423 - mse: 0.1423
3021/3021 [==============================] - 1s 171us/sample - loss: 0.1543 - mse: 0.1543 - val_loss: 0.1354 - val_mse: 0.1354
Epoch 24/100
100/3021 [..............................] - ETA: 0s - loss: 0.1893 - mse: 0.1893
1200/3021 [==========>...................] - ETA: 0s - loss: 0.1713 - mse: 0.1713
3000/3021 [============================>.] - ETA: 0s - loss: 0.1620 - mse: 0.1620
3021/3021 [==============================] - 1s 192us/sample - loss: 0.1615 - mse: 0.1615 - val_loss: 0.1031 - val_mse: 0.1031
Epoch 25/100
100/3021 [..............................] - ETA: 0s - loss: 0.1419 - mse: 0.1419
1600/3021 [==============>...............] - ETA: 0s - loss: 0.1293 - mse: 0.1293
2900/3021 [===========================>..] - ETA: 0s - loss: 0.1159 - mse: 0.1159
3021/3021 [==============================] - 1s 192us/sample - loss: 0.1149 - mse: 0.1149 - val_loss: 0.0649 - val_mse: 0.0649
Epoch 26/100
100/3021 [..............................] - ETA: 0s - loss: 0.0889 - mse: 0.0889
1800/3021 [================>.............] - ETA: 0s - loss: 0.1033 - mse: 0.1033
3021/3021 [==============================] - 1s 194us/sample - loss: 0.1099 - mse: 0.1099 - val_loss: 0.0625 - val_mse: 0.0625
Epoch 27/100
100/3021 [..............................] - ETA: 0s - loss: 0.1077 - mse: 0.1077
1500/3021 [=============>................] - ETA: 0s - loss: 0.1499 - mse: 0.1499
3021/3021 [==============================] - 1s 180us/sample - loss: 0.1787 - mse: 0.1787 - val_loss: 0.1726 - val_mse: 0.1726
Epoch 28/100
100/3021 [..............................] - ETA: 0s - loss: 0.1841 - mse: 0.1841
1800/3021 [================>.............] - ETA: 0s - loss: 0.1694 - mse: 0.1694
3021/3021 [==============================] - 1s 172us/sample - loss: 0.1437 - mse: 0.1437 - val_loss: 0.0700 - val_mse: 0.0700
Epoch 29/100
100/3021 [..............................] - ETA: 0s - loss: 0.0850 - mse: 0.0850
2000/3021 [==================>...........] - ETA: 0s - loss: 0.0880 - mse: 0.0880
3021/3021 [==============================] - 1s 169us/sample - loss: 0.0963 - mse: 0.0963 - val_loss: 0.1600 - val_mse: 0.1600
Epoch 30/100
100/3021 [..............................] - ETA: 0s - loss: 0.2036 - mse: 0.2036
1800/3021 [================>.............] - ETA: 0s - loss: 0.1159 - mse: 0.1159
3021/3021 [==============================] - 1s 173us/sample - loss: 0.1088 - mse: 0.1088 - val_loss: 0.0989 - val_mse: 0.0989
Epoch 31/100
100/3021 [..............................] - ETA: 0s - loss: 0.1567 - mse: 0.1567
1800/3021 [================>.............] - ETA: 0s - loss: 0.1017 - mse: 0.1017
3021/3021 [==============================] - 1s 180us/sample - loss: 0.0946 - mse: 0.0946 - val_loss: 0.0586 - val_mse: 0.0586
Epoch 32/100
100/3021 [..............................] - ETA: 0s - loss: 0.0714 - mse: 0.0714
1900/3021 [=================>............] - ETA: 0s - loss: 0.0795 - mse: 0.0795
3021/3021 [==============================] - 1s 175us/sample - loss: 0.0833 - mse: 0.0833 - val_loss: 0.1905 - val_mse: 0.1905
Epoch 33/100
100/3021 [..............................] - ETA: 0s - loss: 0.1904 - mse: 0.1904
1900/3021 [=================>............] - ETA: 0s - loss: 0.1507 - mse: 0.1507
3021/3021 [==============================] - 1s 182us/sample - loss: 0.1262 - mse: 0.1262 - val_loss: 0.0708 - val_mse: 0.0708
Epoch 34/100
100/3021 [..............................] - ETA: 0s - loss: 0.0985 - mse: 0.0985
1700/3021 [===============>..............] - ETA: 0s - loss: 0.0743 - mse: 0.0743
3021/3021 [==============================] - 1s 176us/sample - loss: 0.0714 - mse: 0.0714 - val_loss: 0.0830 - val_mse: 0.0830
Epoch 35/100
100/3021 [..............................] - ETA: 0s - loss: 0.1220 - mse: 0.1220
1900/3021 [=================>............] - ETA: 0s - loss: 0.0694 - mse: 0.0694
3021/3021 [==============================] - 1s 170us/sample - loss: 0.0665 - mse: 0.0665 - val_loss: 0.0508 - val_mse: 0.0508
Epoch 36/100
100/3021 [..............................] - ETA: 0s - loss: 0.0614 - mse: 0.0614
1900/3021 [=================>............] - ETA: 0s - loss: 0.0562 - mse: 0.0562
3021/3021 [==============================] - 1s 167us/sample - loss: 0.0682 - mse: 0.0682 - val_loss: 0.0734 - val_mse: 0.0734
Epoch 37/100
100/3021 [..............................] - ETA: 0s - loss: 0.0587 - mse: 0.0587
1300/3021 [===========>..................] - ETA: 0s - loss: 0.0709 - mse: 0.0709
3021/3021 [==============================] - 1s 172us/sample - loss: 0.0780 - mse: 0.0780 - val_loss: 0.0626 - val_mse: 0.0626
Epoch 38/100
100/3021 [..............................] - ETA: 0s - loss: 0.0572 - mse: 0.0572
1800/3021 [================>.............] - ETA: 0s - loss: 0.0583 - mse: 0.0583
3021/3021 [==============================] - 0s 156us/sample - loss: 0.0616 - mse: 0.0616 - val_loss: 0.0943 - val_mse: 0.0943
Epoch 39/100
100/3021 [..............................] - ETA: 0s - loss: 0.0862 - mse: 0.0862
1600/3021 [==============>...............] - ETA: 0s - loss: 0.0902 - mse: 0.0902
3021/3021 [==============================] - 0s 165us/sample - loss: 0.0861 - mse: 0.0861 - val_loss: 0.0484 - val_mse: 0.0484
Epoch 40/100
100/3021 [..............................] - ETA: 0s - loss: 0.0514 - mse: 0.0514
1900/3021 [=================>............] - ETA: 0s - loss: 0.0841 - mse: 0.0841
3021/3021 [==============================] - 1s 166us/sample - loss: 0.0743 - mse: 0.0743 - val_loss: 0.0611 - val_mse: 0.0611
Epoch 41/100
100/3021 [..............................] - ETA: 0s - loss: 0.0759 - mse: 0.0759
1200/3021 [==========>...................] - ETA: 0s - loss: 0.0652 - mse: 0.0652
3021/3021 [==============================] - 0s 164us/sample - loss: 0.0576 - mse: 0.0576 - val_loss: 0.0595 - val_mse: 0.0595
Epoch 42/100
100/3021 [..............................] - ETA: 0s - loss: 0.0521 - mse: 0.0521
1400/3021 [============>.................] - ETA: 0s - loss: 0.0618 - mse: 0.0618
3021/3021 [==============================] - 1s 174us/sample - loss: 0.0547 - mse: 0.0547 - val_loss: 0.0445 - val_mse: 0.0445
Epoch 43/100
100/3021 [..............................] - ETA: 0s - loss: 0.0433 - mse: 0.0433
1900/3021 [=================>............] - ETA: 0s - loss: 0.0551 - mse: 0.0551
3021/3021 [==============================] - 1s 178us/sample - loss: 0.0535 - mse: 0.0535 - val_loss: 0.0522 - val_mse: 0.0522
Epoch 44/100
100/3021 [..............................] - ETA: 0s - loss: 0.0594 - mse: 0.0594
1800/3021 [================>.............] - ETA: 0s - loss: 0.0494 - mse: 0.0494
3021/3021 [==============================] - 1s 187us/sample - loss: 0.0544 - mse: 0.0544 - val_loss: 0.0545 - val_mse: 0.0545
Epoch 45/100
100/3021 [..............................] - ETA: 0s - loss: 0.0441 - mse: 0.0441
1500/3021 [=============>................] - ETA: 0s - loss: 0.0542 - mse: 0.0542
3021/3021 [==============================] - 0s 159us/sample - loss: 0.0534 - mse: 0.0534 - val_loss: 0.0715 - val_mse: 0.0715
Epoch 46/100
100/3021 [..............................] - ETA: 0s - loss: 0.0753 - mse: 0.0753
2300/3021 [=====================>........] - ETA: 0s - loss: 0.0510 - mse: 0.0510
3021/3021 [==============================] - 0s 155us/sample - loss: 0.0493 - mse: 0.0493 - val_loss: 0.0348 - val_mse: 0.0348
Epoch 47/100
100/3021 [..............................] - ETA: 0s - loss: 0.0353 - mse: 0.0353
2100/3021 [===================>..........] - ETA: 0s - loss: 0.0415 - mse: 0.0415
3021/3021 [==============================] - 0s 165us/sample - loss: 0.0434 - mse: 0.0434 - val_loss: 0.0417 - val_mse: 0.0417
Epoch 48/100
100/3021 [..............................] - ETA: 0s - loss: 0.0545 - mse: 0.0545
2100/3021 [===================>..........] - ETA: 0s - loss: 0.0634 - mse: 0.0634
3021/3021 [==============================] - 0s 161us/sample - loss: 0.0625 - mse: 0.0625 - val_loss: 0.0438 - val_mse: 0.0438
Epoch 49/100
100/3021 [..............................] - ETA: 0s - loss: 0.0345 - mse: 0.0345
1900/3021 [=================>............] - ETA: 0s - loss: 0.0543 - mse: 0.0543
3021/3021 [==============================] - 1s 166us/sample - loss: 0.0590 - mse: 0.0590 - val_loss: 0.0667 - val_mse: 0.0667
Epoch 50/100
100/3021 [..............................] - ETA: 0s - loss: 0.0621 - mse: 0.0621
1300/3021 [===========>..................] - ETA: 0s - loss: 0.0628 - mse: 0.0628
3021/3021 [==============================] - 0s 162us/sample - loss: 0.0576 - mse: 0.0576 - val_loss: 0.0636 - val_mse: 0.0636
Epoch 51/100
100/3021 [..............................] - ETA: 0s - loss: 0.0596 - mse: 0.0596
1500/3021 [=============>................] - ETA: 0s - loss: 0.0471 - mse: 0.0471
3021/3021 [==============================] - 0s 165us/sample - loss: 0.0441 - mse: 0.0441 - val_loss: 0.1476 - val_mse: 0.1476
Epoch 52/100
100/3021 [..............................] - ETA: 0s - loss: 0.1577 - mse: 0.1577
2200/3021 [====================>.........] - ETA: 0s - loss: 0.0783 - mse: 0.0783
3021/3021 [==============================] - 1s 169us/sample - loss: 0.0700 - mse: 0.0700 - val_loss: 0.0433 - val_mse: 0.0433
Epoch 53/100
100/3021 [..............................] - ETA: 0s - loss: 0.0709 - mse: 0.0709
2100/3021 [===================>..........] - ETA: 0s - loss: 0.0487 - mse: 0.0487
3021/3021 [==============================] - 1s 176us/sample - loss: 0.0473 - mse: 0.0473 - val_loss: 0.0465 - val_mse: 0.0465
Epoch 54/100
100/3021 [..............................] - ETA: 0s - loss: 0.0440 - mse: 0.0440
1400/3021 [============>.................] - ETA: 0s - loss: 0.0486 - mse: 0.0486
3021/3021 [==============================] - 0s 157us/sample - loss: 0.0504 - mse: 0.0504 - val_loss: 0.0754 - val_mse: 0.0754
Epoch 55/100
100/3021 [..............................] - ETA: 0s - loss: 0.0467 - mse: 0.0467
2400/3021 [======================>.......] - ETA: 0s - loss: 0.0804 - mse: 0.0804
3021/3021 [==============================] - 0s 158us/sample - loss: 0.0743 - mse: 0.0743 - val_loss: 0.0459 - val_mse: 0.0459
Epoch 56/100
100/3021 [..............................] - ETA: 0s - loss: 0.0409 - mse: 0.0409
1800/3021 [================>.............] - ETA: 0s - loss: 0.0453 - mse: 0.0453
3021/3021 [==============================] - 0s 159us/sample - loss: 0.0438 - mse: 0.0438 - val_loss: 0.0557 - val_mse: 0.0557
Epoch 57/100
100/3021 [..............................] - ETA: 0s - loss: 0.0473 - mse: 0.0473
1100/3021 [=========>....................] - ETA: 0s - loss: 0.0597 - mse: 0.0597
3021/3021 [==============================] - 1s 166us/sample - loss: 0.0545 - mse: 0.0545 - val_loss: 0.0452 - val_mse: 0.0452
Epoch 58/100
100/3021 [..............................] - ETA: 0s - loss: 0.0383 - mse: 0.0383
2100/3021 [===================>..........] - ETA: 0s - loss: 0.0406 - mse: 0.0406
3021/3021 [==============================] - 1s 166us/sample - loss: 0.0428 - mse: 0.0428 - val_loss: 0.0542 - val_mse: 0.0542
Epoch 59/100
100/3021 [..............................] - ETA: 0s - loss: 0.0386 - mse: 0.0386
1300/3021 [===========>..................] - ETA: 0s - loss: 0.0440 - mse: 0.0440
3021/3021 [==============================] - 0s 164us/sample - loss: 0.0415 - mse: 0.0415 - val_loss: 0.0377 - val_mse: 0.0377
Epoch 60/100
100/3021 [..............................] - ETA: 0s - loss: 0.0345 - mse: 0.0345
1900/3021 [=================>............] - ETA: 0s - loss: 0.0487 - mse: 0.0487
3021/3021 [==============================] - 0s 160us/sample - loss: 0.0455 - mse: 0.0455 - val_loss: 0.0360 - val_mse: 0.0360
Epoch 61/100
100/3021 [..............................] - ETA: 0s - loss: 0.0321 - mse: 0.0321
1300/3021 [===========>..................] - ETA: 0s - loss: 0.0425 - mse: 0.0425
3021/3021 [==============================] - 0s 159us/sample - loss: 0.0427 - mse: 0.0427 - val_loss: 0.0380 - val_mse: 0.0380
Epoch 62/100
100/3021 [..............................] - ETA: 0s - loss: 0.0337 - mse: 0.0337
1900/3021 [=================>............] - ETA: 0s - loss: 0.0436 - mse: 0.0436
3021/3021 [==============================] - 0s 151us/sample - loss: 0.0464 - mse: 0.0464 - val_loss: 0.0625 - val_mse: 0.0625
Epoch 63/100
100/3021 [..............................] - ETA: 0s - loss: 0.0432 - mse: 0.0432
2400/3021 [======================>.......] - ETA: 0s - loss: 0.0469 - mse: 0.0469
3021/3021 [==============================] - 0s 151us/sample - loss: 0.0453 - mse: 0.0453 - val_loss: 0.0564 - val_mse: 0.0564
Epoch 64/100
100/3021 [..............................] - ETA: 0s - loss: 0.0364 - mse: 0.0364
2100/3021 [===================>..........] - ETA: 0s - loss: 0.0448 - mse: 0.0448
3021/3021 [==============================] - 0s 159us/sample - loss: 0.0441 - mse: 0.0441 - val_loss: 0.0443 - val_mse: 0.0443
Epoch 65/100
100/3021 [..............................] - ETA: 0s - loss: 0.0506 - mse: 0.0506
1900/3021 [=================>............] - ETA: 0s - loss: 0.0535 - mse: 0.0535
3021/3021 [==============================] - 0s 159us/sample - loss: 0.0483 - mse: 0.0483 - val_loss: 0.0387 - val_mse: 0.0387
Epoch 66/100
100/3021 [..............................] - ETA: 0s - loss: 0.0453 - mse: 0.0453
2200/3021 [====================>.........] - ETA: 0s - loss: 0.0608 - mse: 0.0608
3021/3021 [==============================] - 0s 158us/sample - loss: 0.0576 - mse: 0.0576 - val_loss: 0.0471 - val_mse: 0.0471
Epoch 67/100
100/3021 [..............................] - ETA: 0s - loss: 0.0406 - mse: 0.0406
1900/3021 [=================>............] - ETA: 0s - loss: 0.0441 - mse: 0.0441
3021/3021 [==============================] - 0s 163us/sample - loss: 0.0449 - mse: 0.0449 - val_loss: 0.0529 - val_mse: 0.0529
Epoch 68/100
100/3021 [..............................] - ETA: 0s - loss: 0.0362 - mse: 0.0362
2100/3021 [===================>..........] - ETA: 0s - loss: 0.0396 - mse: 0.0396
3021/3021 [==============================] - 0s 158us/sample - loss: 0.0405 - mse: 0.0405 - val_loss: 0.0595 - val_mse: 0.0595
Epoch 69/100
100/3021 [..............................] - ETA: 0s - loss: 0.0594 - mse: 0.0594
1700/3021 [===============>..............] - ETA: 0s - loss: 0.0559 - mse: 0.0559
3021/3021 [==============================] - 0s 156us/sample - loss: 0.0513 - mse: 0.0513 - val_loss: 0.0795 - val_mse: 0.0795
Epoch 70/100
100/3021 [..............................] - ETA: 0s - loss: 0.0526 - mse: 0.0526
2300/3021 [=====================>........] - ETA: 0s - loss: 0.0605 - mse: 0.0605
3021/3021 [==============================] - 0s 154us/sample - loss: 0.0590 - mse: 0.0590 - val_loss: 0.0369 - val_mse: 0.0369
Epoch 71/100
100/3021 [..............................] - ETA: 0s - loss: 0.0248 - mse: 0.0248
1800/3021 [================>.............] - ETA: 0s - loss: 0.0511 - mse: 0.0511
3021/3021 [==============================] - 0s 159us/sample - loss: 0.0560 - mse: 0.0560 - val_loss: 0.0401 - val_mse: 0.0401
Epoch 72/100
100/3021 [..............................] - ETA: 0s - loss: 0.0384 - mse: 0.0384
2000/3021 [==================>...........] - ETA: 0s - loss: 0.0573 - mse: 0.0573
3021/3021 [==============================] - 0s 160us/sample - loss: 0.0558 - mse: 0.0558 - val_loss: 0.0729 - val_mse: 0.0729
Epoch 73/100
100/3021 [..............................] - ETA: 0s - loss: 0.0426 - mse: 0.0426
1300/3021 [===========>..................] - ETA: 0s - loss: 0.0709 - mse: 0.0709
3021/3021 [==============================] - 0s 163us/sample - loss: 0.0720 - mse: 0.0720 - val_loss: 0.0434 - val_mse: 0.0434
Epoch 74/100
100/3021 [..............................] - ETA: 0s - loss: 0.0530 - mse: 0.0530
2200/3021 [====================>.........] - ETA: 0s - loss: 0.0906 - mse: 0.0906
3021/3021 [==============================] - 0s 154us/sample - loss: 0.0864 - mse: 0.0864 - val_loss: 0.0952 - val_mse: 0.0952
Epoch 75/100
100/3021 [..............................] - ETA: 0s - loss: 0.0778 - mse: 0.0778
1900/3021 [=================>............] - ETA: 0s - loss: 0.0829 - mse: 0.0829
3021/3021 [==============================] - 0s 151us/sample - loss: 0.0745 - mse: 0.0745 - val_loss: 0.0507 - val_mse: 0.0507
Epoch 76/100
100/3021 [..............................] - ETA: 0s - loss: 0.0430 - mse: 0.0430
2000/3021 [==================>...........] - ETA: 0s - loss: 0.0503 - mse: 0.0503
3000/3021 [============================>.] - ETA: 0s - loss: 0.0519 - mse: 0.0519
3021/3021 [==============================] - 1s 174us/sample - loss: 0.0519 - mse: 0.0519 - val_loss: 0.0684 - val_mse: 0.0684
Epoch 77/100
100/3021 [..............................] - ETA: 0s - loss: 0.0647 - mse: 0.0647
1800/3021 [================>.............] - ETA: 0s - loss: 0.0580 - mse: 0.0580
3021/3021 [==============================] - 0s 163us/sample - loss: 0.0566 - mse: 0.0566 - val_loss: 0.0509 - val_mse: 0.0509
Epoch 78/100
100/3021 [..............................] - ETA: 0s - loss: 0.0530 - mse: 0.0530
1700/3021 [===============>..............] - ETA: 0s - loss: 0.0482 - mse: 0.0482
3021/3021 [==============================] - 0s 161us/sample - loss: 0.0517 - mse: 0.0517 - val_loss: 0.0507 - val_mse: 0.0507
Epoch 79/100
100/3021 [..............................] - ETA: 0s - loss: 0.0628 - mse: 0.0628
2000/3021 [==================>...........] - ETA: 0s - loss: 0.0553 - mse: 0.0553
3021/3021 [==============================] - 0s 153us/sample - loss: 0.0559 - mse: 0.0559 - val_loss: 0.2806 - val_mse: 0.2806
Epoch 80/100
100/3021 [..............................] - ETA: 0s - loss: 0.2932 - mse: 0.2932
2100/3021 [===================>..........] - ETA: 0s - loss: 0.1208 - mse: 0.1208
3021/3021 [==============================] - 0s 164us/sample - loss: 0.1175 - mse: 0.1175 - val_loss: 0.1618 - val_mse: 0.1618
Epoch 81/100
100/3021 [..............................] - ETA: 0s - loss: 0.1828 - mse: 0.1828
1500/3021 [=============>................] - ETA: 0s - loss: 0.1378 - mse: 0.1378
3021/3021 [==============================] - 0s 162us/sample - loss: 0.1455 - mse: 0.1455 - val_loss: 0.1710 - val_mse: 0.1710
Epoch 82/100
100/3021 [..............................] - ETA: 0s - loss: 0.1745 - mse: 0.1745
1800/3021 [================>.............] - ETA: 0s - loss: 0.1312 - mse: 0.1312
3021/3021 [==============================] - 0s 152us/sample - loss: 0.1204 - mse: 0.1204 - val_loss: 0.0822 - val_mse: 0.0822
Epoch 83/100
100/3021 [..............................] - ETA: 0s - loss: 0.1109 - mse: 0.1109
2200/3021 [====================>.........] - ETA: 0s - loss: 0.0952 - mse: 0.0952
3021/3021 [==============================] - 0s 154us/sample - loss: 0.1090 - mse: 0.1090 - val_loss: 0.0940 - val_mse: 0.0940
Epoch 84/100
100/3021 [..............................] - ETA: 0s - loss: 0.0481 - mse: 0.0481
1800/3021 [================>.............] - ETA: 0s - loss: 0.1222 - mse: 0.1222
3021/3021 [==============================] - 0s 164us/sample - loss: 0.1132 - mse: 0.1132 - val_loss: 0.1357 - val_mse: 0.1357
Epoch 85/100
100/3021 [..............................] - ETA: 0s - loss: 0.1482 - mse: 0.1482
2000/3021 [==================>...........] - ETA: 0s - loss: 0.1359 - mse: 0.1359
3021/3021 [==============================] - 0s 158us/sample - loss: 0.1489 - mse: 0.1489 - val_loss: 0.1436 - val_mse: 0.1436
Epoch 86/100
100/3021 [..............................] - ETA: 0s - loss: 0.2053 - mse: 0.2053
2000/3021 [==================>...........] - ETA: 0s - loss: 0.1177 - mse: 0.1177
3021/3021 [==============================] - 0s 163us/sample - loss: 0.1056 - mse: 0.1056 - val_loss: 0.0964 - val_mse: 0.0964
Epoch 87/100
100/3021 [..............................] - ETA: 0s - loss: 0.0696 - mse: 0.0696
2100/3021 [===================>..........] - ETA: 0s - loss: 0.0778 - mse: 0.0778
3021/3021 [==============================] - 0s 162us/sample - loss: 0.0797 - mse: 0.0797 - val_loss: 0.1402 - val_mse: 0.1402
Epoch 88/100
100/3021 [..............................] - ETA: 0s - loss: 0.1746 - mse: 0.1746
1700/3021 [===============>..............] - ETA: 0s - loss: 0.1046 - mse: 0.1046
3021/3021 [==============================] - 1s 169us/sample - loss: 0.1046 - mse: 0.1046 - val_loss: 0.0568 - val_mse: 0.0568
Epoch 89/100
100/3021 [..............................] - ETA: 0s - loss: 0.0572 - mse: 0.0572
1100/3021 [=========>....................] - ETA: 0s - loss: 0.0907 - mse: 0.0907
2500/3021 [=======================>......] - ETA: 0s - loss: 0.0979 - mse: 0.0979
3021/3021 [==============================] - 1s 187us/sample - loss: 0.0967 - mse: 0.0967 - val_loss: 0.1607 - val_mse: 0.1607
Epoch 90/100
100/3021 [..............................] - ETA: 0s - loss: 0.1609 - mse: 0.1609
2200/3021 [====================>.........] - ETA: 0s - loss: 0.1037 - mse: 0.1037
3021/3021 [==============================] - 0s 165us/sample - loss: 0.0970 - mse: 0.0970 - val_loss: 0.0889 - val_mse: 0.0889
Epoch 91/100
100/3021 [..............................] - ETA: 0s - loss: 0.1179 - mse: 0.1179
2100/3021 [===================>..........] - ETA: 0s - loss: 0.0840 - mse: 0.0840
3021/3021 [==============================] - 0s 158us/sample - loss: 0.0815 - mse: 0.0815 - val_loss: 0.0612 - val_mse: 0.0612
Epoch 92/100
100/3021 [..............................] - ETA: 0s - loss: 0.0624 - mse: 0.0624
2200/3021 [====================>.........] - ETA: 0s - loss: 0.0671 - mse: 0.0671
3021/3021 [==============================] - 1s 176us/sample - loss: 0.0637 - mse: 0.0637 - val_loss: 0.0527 - val_mse: 0.0527
Epoch 93/100
100/3021 [..............................] - ETA: 0s - loss: 0.0527 - mse: 0.0527
1600/3021 [==============>...............] - ETA: 0s - loss: 0.0663 - mse: 0.0663
3021/3021 [==============================] - 1s 177us/sample - loss: 0.0721 - mse: 0.0721 - val_loss: 0.1012 - val_mse: 0.1012
Epoch 94/100
100/3021 [..............................] - ETA: 0s - loss: 0.0940 - mse: 0.0940
1700/3021 [===============>..............] - ETA: 0s - loss: 0.0972 - mse: 0.0972
3021/3021 [==============================] - 1s 186us/sample - loss: 0.0867 - mse: 0.0867 - val_loss: 0.0683 - val_mse: 0.0683
Epoch 95/100
100/3021 [..............................] - ETA: 0s - loss: 0.0536 - mse: 0.0536
1800/3021 [================>.............] - ETA: 0s - loss: 0.0724 - mse: 0.0724
3021/3021 [==============================] - 1s 175us/sample - loss: 0.0651 - mse: 0.0651 - val_loss: 0.0809 - val_mse: 0.0809
Epoch 96/100
100/3021 [..............................] - ETA: 0s - loss: 0.0704 - mse: 0.0704
1500/3021 [=============>................] - ETA: 0s - loss: 0.0677 - mse: 0.0677
3021/3021 [==============================] - 1s 175us/sample - loss: 0.0746 - mse: 0.0746 - val_loss: 0.1105 - val_mse: 0.1105
Epoch 97/100
100/3021 [..............................] - ETA: 0s - loss: 0.0907 - mse: 0.0907
1900/3021 [=================>............] - ETA: 0s - loss: 0.0855 - mse: 0.0855
3021/3021 [==============================] - 1s 174us/sample - loss: 0.0792 - mse: 0.0792 - val_loss: 0.0773 - val_mse: 0.0773
Epoch 98/100
100/3021 [..............................] - ETA: 0s - loss: 0.0696 - mse: 0.0696
2000/3021 [==================>...........] - ETA: 0s - loss: 0.0665 - mse: 0.0665
3021/3021 [==============================] - 0s 160us/sample - loss: 0.0671 - mse: 0.0671 - val_loss: 0.1188 - val_mse: 0.1188
Epoch 99/100
100/3021 [..............................] - ETA: 0s - loss: 0.0961 - mse: 0.0961
2000/3021 [==================>...........] - ETA: 0s - loss: 0.0867 - mse: 0.0867
3021/3021 [==============================] - 0s 158us/sample - loss: 0.0915 - mse: 0.0915 - val_loss: 0.1361 - val_mse: 0.1361
Epoch 100/100
100/3021 [..............................] - ETA: 0s - loss: 0.1718 - mse: 0.1718
1600/3021 [==============>...............] - ETA: 0s - loss: 0.1049 - mse: 0.1049
3021/3021 [==============================] - 1s 175us/sample - loss: 0.0955 - mse: 0.0955 - val_loss: 0.1316 - val_mse: 0.1316Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-05-04T01-15-27Z
Training run 46/46 (flags = list(64, 128, 1e-04, 200, 100, "sigmoid", "sigmoid", 0.1, 0.2))
Using run directory runs/2020-05-04T01-16-22Z
> FLAGS <- flags(
+ flag_numeric("nodes1", 128),
+ flag_numeric("nodes2", 128),
+ flag_numeric("batch_size", 100),
+ flag_string("activation1" .... [TRUNCATED]
> model = keras_model_sequential()
> model %>%
+ layer_dense(units=FLAGS$nodes1, activation=FLAGS$activation1, input_shape=dim(efw_train2)[2]) %>%
+ layer_dropout(FLAGS$dropout1) %> .... [TRUNCATED]
> model %>% compile(
+ optimizer = optimizer_adam(lr=FLAGS$learning_rate),
+ loss = 'mse',
+ metrics = c('mse')
+ )
> model %>% fit(
+ as.matrix(efw_train2), train2Label,
+ epochs=FLAGS$epochs,
+ batch_size=FLAGS$batch_size,
+ validation_data=list(as.matrix( .... [TRUNCATED]
Train on 3021 samples, validate on 334 samples
Epoch 1/100
200/3021 [>.............................] - ETA: 4s - loss: 48.0042 - mse: 48.0042
3021/3021 [==============================] - 1s 287us/sample - loss: 46.5156 - mse: 46.5156 - val_loss: 46.2916 - val_mse: 46.2916
Epoch 2/100
200/3021 [>.............................] - ETA: 0s - loss: 45.3137 - mse: 45.3137
3000/3021 [============================>.] - ETA: 0s - loss: 45.6664 - mse: 45.6664
3021/3021 [==============================] - 1s 189us/sample - loss: 45.6400 - mse: 45.6400 - val_loss: 45.4306 - val_mse: 45.4306
Epoch 3/100
200/3021 [>.............................] - ETA: 0s - loss: 45.4874 - mse: 45.4874
3021/3021 [==============================] - 0s 160us/sample - loss: 44.6796 - mse: 44.6795 - val_loss: 44.5849 - val_mse: 44.5849
Epoch 4/100
200/3021 [>.............................] - ETA: 0s - loss: 44.9633 - mse: 44.9633
3021/3021 [==============================] - 0s 138us/sample - loss: 43.9527 - mse: 43.9527 - val_loss: 43.7469 - val_mse: 43.7469
Epoch 5/100
200/3021 [>.............................] - ETA: 0s - loss: 42.8629 - mse: 42.8629
3000/3021 [============================>.] - ETA: 0s - loss: 42.7921 - mse: 42.7921
3021/3021 [==============================] - 0s 148us/sample - loss: 42.8047 - mse: 42.8047 - val_loss: 42.9213 - val_mse: 42.9213
Epoch 6/100
200/3021 [>.............................] - ETA: 0s - loss: 42.5380 - mse: 42.5380
2200/3021 [====================>.........] - ETA: 0s - loss: 42.3588 - mse: 42.3588
3021/3021 [==============================] - 0s 146us/sample - loss: 42.1150 - mse: 42.1150 - val_loss: 42.1157 - val_mse: 42.1157
Epoch 7/100
200/3021 [>.............................] - ETA: 0s - loss: 41.2788 - mse: 41.2788
2200/3021 [====================>.........] - ETA: 0s - loss: 41.4296 - mse: 41.4296
3021/3021 [==============================] - 0s 149us/sample - loss: 41.2561 - mse: 41.2561 - val_loss: 41.3279 - val_mse: 41.3279
Epoch 8/100
200/3021 [>.............................] - ETA: 0s - loss: 41.8496 - mse: 41.8496
3021/3021 [==============================] - 0s 156us/sample - loss: 40.6164 - mse: 40.6164 - val_loss: 40.5457 - val_mse: 40.5457
Epoch 9/100
200/3021 [>.............................] - ETA: 0s - loss: 39.8364 - mse: 39.8364
2800/3021 [==========================>...] - ETA: 0s - loss: 39.7120 - mse: 39.7120
3021/3021 [==============================] - 0s 155us/sample - loss: 39.7064 - mse: 39.7064 - val_loss: 39.7801 - val_mse: 39.7801
Epoch 10/100
200/3021 [>.............................] - ETA: 0s - loss: 39.0969 - mse: 39.0969
3000/3021 [============================>.] - ETA: 0s - loss: 39.0084 - mse: 39.0084
3021/3021 [==============================] - 1s 180us/sample - loss: 38.9888 - mse: 38.9888 - val_loss: 39.0297 - val_mse: 39.0297
Epoch 11/100
200/3021 [>.............................] - ETA: 0s - loss: 37.6605 - mse: 37.6605
3021/3021 [==============================] - 0s 152us/sample - loss: 38.1766 - mse: 38.1766 - val_loss: 38.2909 - val_mse: 38.2909
Epoch 12/100
200/3021 [>.............................] - ETA: 0s - loss: 38.0392 - mse: 38.0392
3021/3021 [==============================] - 0s 151us/sample - loss: 37.4091 - mse: 37.4091 - val_loss: 37.5575 - val_mse: 37.5575
Epoch 13/100
200/3021 [>.............................] - ETA: 0s - loss: 37.7228 - mse: 37.7228
3021/3021 [==============================] - 0s 149us/sample - loss: 36.7641 - mse: 36.7641 - val_loss: 36.8336 - val_mse: 36.8336
Epoch 14/100
200/3021 [>.............................] - ETA: 0s - loss: 36.6522 - mse: 36.6522
3021/3021 [==============================] - 0s 146us/sample - loss: 36.0921 - mse: 36.0921 - val_loss: 36.1237 - val_mse: 36.1237
Epoch 15/100
200/3021 [>.............................] - ETA: 0s - loss: 35.9718 - mse: 35.9718
3021/3021 [==============================] - 0s 141us/sample - loss: 35.4065 - mse: 35.4065 - val_loss: 35.4259 - val_mse: 35.4259
Epoch 16/100
200/3021 [>.............................] - ETA: 0s - loss: 34.4152 - mse: 34.4152
3021/3021 [==============================] - 0s 143us/sample - loss: 34.7017 - mse: 34.7017 - val_loss: 34.7377 - val_mse: 34.7377
Epoch 17/100
200/3021 [>.............................] - ETA: 0s - loss: 34.3446 - mse: 34.3446
3021/3021 [==============================] - 0s 143us/sample - loss: 34.0267 - mse: 34.0267 - val_loss: 34.0588 - val_mse: 34.0588
Epoch 18/100
200/3021 [>.............................] - ETA: 0s - loss: 33.3819 - mse: 33.3819
3021/3021 [==============================] - 0s 138us/sample - loss: 33.2513 - mse: 33.2513 - val_loss: 33.3895 - val_mse: 33.3895
Epoch 19/100
200/3021 [>.............................] - ETA: 0s - loss: 32.6648 - mse: 32.6648
3021/3021 [==============================] - 0s 146us/sample - loss: 32.5886 - mse: 32.5886 - val_loss: 32.7328 - val_mse: 32.7328
Epoch 20/100
200/3021 [>.............................] - ETA: 0s - loss: 31.7736 - mse: 31.7736
3021/3021 [==============================] - 0s 141us/sample - loss: 31.9913 - mse: 31.9913 - val_loss: 32.0829 - val_mse: 32.0829
Epoch 21/100
200/3021 [>.............................] - ETA: 0s - loss: 31.3027 - mse: 31.3027
3021/3021 [==============================] - 1s 176us/sample - loss: 31.3777 - mse: 31.3777 - val_loss: 31.4459 - val_mse: 31.4459
Epoch 22/100
200/3021 [>.............................] - ETA: 0s - loss: 31.3509 - mse: 31.3509
3021/3021 [==============================] - 0s 148us/sample - loss: 30.6344 - mse: 30.6344 - val_loss: 30.8181 - val_mse: 30.8181
Epoch 23/100
200/3021 [>.............................] - ETA: 0s - loss: 30.3432 - mse: 30.3432
3021/3021 [==============================] - 0s 145us/sample - loss: 29.9597 - mse: 29.9597 - val_loss: 30.1978 - val_mse: 30.1978
Epoch 24/100
200/3021 [>.............................] - ETA: 0s - loss: 29.8676 - mse: 29.8676
3021/3021 [==============================] - 0s 144us/sample - loss: 29.3661 - mse: 29.3661 - val_loss: 29.5894 - val_mse: 29.5894
Epoch 25/100
200/3021 [>.............................] - ETA: 0s - loss: 29.1818 - mse: 29.1818
3021/3021 [==============================] - 0s 155us/sample - loss: 28.8362 - mse: 28.8362 - val_loss: 28.9902 - val_mse: 28.9902
Epoch 26/100
200/3021 [>.............................] - ETA: 0s - loss: 28.3524 - mse: 28.3524
3021/3021 [==============================] - 0s 138us/sample - loss: 28.1544 - mse: 28.1544 - val_loss: 28.3968 - val_mse: 28.3968
Epoch 27/100
200/3021 [>.............................] - ETA: 0s - loss: 28.0149 - mse: 28.0149
3021/3021 [==============================] - 0s 138us/sample - loss: 27.6246 - mse: 27.6246 - val_loss: 27.8137 - val_mse: 27.8137
Epoch 28/100
200/3021 [>.............................] - ETA: 0s - loss: 27.8595 - mse: 27.8595
3021/3021 [==============================] - 0s 142us/sample - loss: 26.9711 - mse: 26.9711 - val_loss: 27.2344 - val_mse: 27.2344
Epoch 29/100
200/3021 [>.............................] - ETA: 0s - loss: 26.2360 - mse: 26.2360
3000/3021 [============================>.] - ETA: 0s - loss: 26.4729 - mse: 26.4729
3021/3021 [==============================] - 0s 143us/sample - loss: 26.4708 - mse: 26.4708 - val_loss: 26.6702 - val_mse: 26.6702
Epoch 30/100
200/3021 [>.............................] - ETA: 0s - loss: 26.4784 - mse: 26.4784
3021/3021 [==============================] - 0s 137us/sample - loss: 25.9921 - mse: 25.9921 - val_loss: 26.1107 - val_mse: 26.1107
Epoch 31/100
200/3021 [>.............................] - ETA: 0s - loss: 25.9624 - mse: 25.9624
3021/3021 [==============================] - 0s 140us/sample - loss: 25.3439 - mse: 25.3439 - val_loss: 25.5618 - val_mse: 25.5618
Epoch 32/100
200/3021 [>.............................] - ETA: 0s - loss: 24.4453 - mse: 24.4453
3021/3021 [==============================] - 0s 140us/sample - loss: 24.8207 - mse: 24.8207 - val_loss: 25.0215 - val_mse: 25.0215
Epoch 33/100
200/3021 [>.............................] - ETA: 0s - loss: 24.3680 - mse: 24.3680
3021/3021 [==============================] - 0s 144us/sample - loss: 24.3800 - mse: 24.3800 - val_loss: 24.4877 - val_mse: 24.4877
Epoch 34/100
200/3021 [>.............................] - ETA: 0s - loss: 24.2719 - mse: 24.2719
3021/3021 [==============================] - 0s 135us/sample - loss: 23.8425 - mse: 23.8425 - val_loss: 23.9576 - val_mse: 23.9576
Epoch 35/100
200/3021 [>.............................] - ETA: 0s - loss: 23.3068 - mse: 23.3068
3021/3021 [==============================] - 0s 140us/sample - loss: 23.1902 - mse: 23.1902 - val_loss: 23.4434 - val_mse: 23.4434
Epoch 36/100
200/3021 [>.............................] - ETA: 0s - loss: 22.6389 - mse: 22.6389
3021/3021 [==============================] - 0s 137us/sample - loss: 22.7759 - mse: 22.7759 - val_loss: 22.9348 - val_mse: 22.9348
Epoch 37/100
200/3021 [>.............................] - ETA: 0s - loss: 22.5350 - mse: 22.5350
3021/3021 [==============================] - 0s 141us/sample - loss: 22.2129 - mse: 22.2129 - val_loss: 22.4342 - val_mse: 22.4342
Epoch 38/100
200/3021 [>.............................] - ETA: 0s - loss: 21.7015 - mse: 21.7015
3021/3021 [==============================] - 0s 138us/sample - loss: 21.7962 - mse: 21.7962 - val_loss: 21.9336 - val_mse: 21.9336
Epoch 39/100
200/3021 [>.............................] - ETA: 0s - loss: 22.0619 - mse: 22.0619
3021/3021 [==============================] - 0s 138us/sample - loss: 21.2627 - mse: 21.2627 - val_loss: 21.4501 - val_mse: 21.4501
Epoch 40/100
200/3021 [>.............................] - ETA: 0s - loss: 21.3144 - mse: 21.3144
3021/3021 [==============================] - 0s 149us/sample - loss: 20.7887 - mse: 20.7887 - val_loss: 20.9712 - val_mse: 20.9712
Epoch 41/100
200/3021 [>.............................] - ETA: 0s - loss: 20.9187 - mse: 20.9187
3021/3021 [==============================] - 0s 144us/sample - loss: 20.3443 - mse: 20.3443 - val_loss: 20.5010 - val_mse: 20.5010
Epoch 42/100
200/3021 [>.............................] - ETA: 0s - loss: 20.4328 - mse: 20.4328
3021/3021 [==============================] - 0s 139us/sample - loss: 19.9094 - mse: 19.9094 - val_loss: 20.0356 - val_mse: 20.0356
Epoch 43/100
200/3021 [>.............................] - ETA: 0s - loss: 19.9531 - mse: 19.9531
3021/3021 [==============================] - 0s 142us/sample - loss: 19.4117 - mse: 19.4117 - val_loss: 19.5779 - val_mse: 19.5779
Epoch 44/100
200/3021 [>.............................] - ETA: 0s - loss: 19.0403 - mse: 19.0403
3021/3021 [==============================] - 0s 141us/sample - loss: 18.9882 - mse: 18.9882 - val_loss: 19.1274 - val_mse: 19.1274
Epoch 45/100
200/3021 [>.............................] - ETA: 0s - loss: 19.0599 - mse: 19.0599
3021/3021 [==============================] - 0s 144us/sample - loss: 18.4770 - mse: 18.4770 - val_loss: 18.6884 - val_mse: 18.6884
Epoch 46/100
200/3021 [>.............................] - ETA: 0s - loss: 18.1298 - mse: 18.1298
3021/3021 [==============================] - 0s 148us/sample - loss: 18.1117 - mse: 18.1117 - val_loss: 18.2520 - val_mse: 18.2520
Epoch 47/100
200/3021 [>.............................] - ETA: 0s - loss: 17.4501 - mse: 17.4501
2600/3021 [========================>.....] - ETA: 0s - loss: 17.6413 - mse: 17.6413
3021/3021 [==============================] - 0s 148us/sample - loss: 17.6495 - mse: 17.6495 - val_loss: 17.8222 - val_mse: 17.8222
Epoch 48/100
200/3021 [>.............................] - ETA: 0s - loss: 17.0807 - mse: 17.0807
3021/3021 [==============================] - 0s 139us/sample - loss: 17.2268 - mse: 17.2268 - val_loss: 17.4032 - val_mse: 17.4032
Epoch 49/100
200/3021 [>.............................] - ETA: 0s - loss: 17.1195 - mse: 17.1195
3021/3021 [==============================] - 0s 146us/sample - loss: 16.9104 - mse: 16.9104 - val_loss: 16.9864 - val_mse: 16.9864
Epoch 50/100
200/3021 [>.............................] - ETA: 0s - loss: 16.3810 - mse: 16.3810
2400/3021 [======================>.......] - ETA: 0s - loss: 16.4584 - mse: 16.4584
3021/3021 [==============================] - 0s 149us/sample - loss: 16.4645 - mse: 16.4645 - val_loss: 16.5783 - val_mse: 16.5783
Epoch 51/100
200/3021 [>.............................] - ETA: 0s - loss: 16.6573 - mse: 16.6573
3021/3021 [==============================] - 0s 147us/sample - loss: 16.0289 - mse: 16.0289 - val_loss: 16.1788 - val_mse: 16.1788
Epoch 52/100
200/3021 [>.............................] - ETA: 0s - loss: 15.9855 - mse: 15.9855
3021/3021 [==============================] - 0s 141us/sample - loss: 15.6131 - mse: 15.6131 - val_loss: 15.7860 - val_mse: 15.7860
Epoch 53/100
200/3021 [>.............................] - ETA: 0s - loss: 15.3110 - mse: 15.3110
3021/3021 [==============================] - 0s 159us/sample - loss: 15.3061 - mse: 15.3061 - val_loss: 15.3991 - val_mse: 15.3991
Epoch 54/100
200/3021 [>.............................] - ETA: 0s - loss: 14.9547 - mse: 14.9547
3021/3021 [==============================] - 0s 151us/sample - loss: 14.8933 - mse: 14.8933 - val_loss: 15.0195 - val_mse: 15.0195
Epoch 55/100
200/3021 [>.............................] - ETA: 0s - loss: 14.7417 - mse: 14.7417
3000/3021 [============================>.] - ETA: 0s - loss: 14.5512 - mse: 14.5512
3021/3021 [==============================] - 0s 150us/sample - loss: 14.5467 - mse: 14.5467 - val_loss: 14.6453 - val_mse: 14.6453
Epoch 56/100
200/3021 [>.............................] - ETA: 0s - loss: 14.7406 - mse: 14.7406
3021/3021 [==============================] - 0s 140us/sample - loss: 14.1732 - mse: 14.1732 - val_loss: 14.2797 - val_mse: 14.2797
Epoch 57/100
200/3021 [>.............................] - ETA: 0s - loss: 13.9856 - mse: 13.9856
3000/3021 [============================>.] - ETA: 0s - loss: 13.8216 - mse: 13.8216
3021/3021 [==============================] - 0s 147us/sample - loss: 13.8168 - mse: 13.8168 - val_loss: 13.9189 - val_mse: 13.9189
Epoch 58/100
200/3021 [>.............................] - ETA: 0s - loss: 14.1539 - mse: 14.1539
3021/3021 [==============================] - 0s 149us/sample - loss: 13.4295 - mse: 13.4295 - val_loss: 13.5665 - val_mse: 13.5665
Epoch 59/100
200/3021 [>.............................] - ETA: 0s - loss: 13.3734 - mse: 13.3734
3021/3021 [==============================] - 0s 142us/sample - loss: 13.1545 - mse: 13.1545 - val_loss: 13.2204 - val_mse: 13.2204
Epoch 60/100
200/3021 [>.............................] - ETA: 0s - loss: 12.5160 - mse: 12.5160
3021/3021 [==============================] - 0s 147us/sample - loss: 12.7770 - mse: 12.7770 - val_loss: 12.8821 - val_mse: 12.8821
Epoch 61/100
200/3021 [>.............................] - ETA: 0s - loss: 12.3617 - mse: 12.3617
3021/3021 [==============================] - 0s 146us/sample - loss: 12.4513 - mse: 12.4513 - val_loss: 12.5448 - val_mse: 12.5448
Epoch 62/100
200/3021 [>.............................] - ETA: 0s - loss: 12.2168 - mse: 12.2168
3021/3021 [==============================] - 0s 143us/sample - loss: 12.0804 - mse: 12.0804 - val_loss: 12.2153 - val_mse: 12.2153
Epoch 63/100
200/3021 [>.............................] - ETA: 0s - loss: 12.0185 - mse: 12.0185
3021/3021 [==============================] - 0s 144us/sample - loss: 11.7583 - mse: 11.7583 - val_loss: 11.8928 - val_mse: 11.8928
Epoch 64/100
200/3021 [>.............................] - ETA: 0s - loss: 11.5484 - mse: 11.5484
3021/3021 [==============================] - 0s 145us/sample - loss: 11.4329 - mse: 11.4329 - val_loss: 11.5759 - val_mse: 11.5759
Epoch 65/100
200/3021 [>.............................] - ETA: 0s - loss: 11.2392 - mse: 11.2392
3021/3021 [==============================] - 0s 142us/sample - loss: 11.1691 - mse: 11.1691 - val_loss: 11.2670 - val_mse: 11.2670
Epoch 66/100
200/3021 [>.............................] - ETA: 0s - loss: 10.9223 - mse: 10.9223
3021/3021 [==============================] - 0s 140us/sample - loss: 10.8397 - mse: 10.8397 - val_loss: 10.9630 - val_mse: 10.9630
Epoch 67/100
200/3021 [>.............................] - ETA: 0s - loss: 10.2321 - mse: 10.2321
3021/3021 [==============================] - 0s 152us/sample - loss: 10.5901 - mse: 10.5901 - val_loss: 10.6639 - val_mse: 10.6639
Epoch 68/100
200/3021 [>.............................] - ETA: 0s - loss: 10.4890 - mse: 10.4890
3021/3021 [==============================] - 0s 144us/sample - loss: 10.3356 - mse: 10.3356 - val_loss: 10.3722 - val_mse: 10.3722
Epoch 69/100
200/3021 [>.............................] - ETA: 0s - loss: 10.2934 - mse: 10.2934
3021/3021 [==============================] - 0s 145us/sample - loss: 9.9594 - mse: 9.9594 - val_loss: 10.0847 - val_mse: 10.0847
Epoch 70/100
200/3021 [>.............................] - ETA: 0s - loss: 9.7414 - mse: 9.7414
2200/3021 [====================>.........] - ETA: 0s - loss: 9.7206 - mse: 9.7206
3021/3021 [==============================] - 0s 147us/sample - loss: 9.6855 - mse: 9.6855 - val_loss: 9.8036 - val_mse: 9.8036
Epoch 71/100
200/3021 [>.............................] - ETA: 0s - loss: 9.8743 - mse: 9.8743
3021/3021 [==============================] - 0s 145us/sample - loss: 9.4107 - mse: 9.4107 - val_loss: 9.5272 - val_mse: 9.5272
Epoch 72/100
200/3021 [>.............................] - ETA: 0s - loss: 9.3045 - mse: 9.3045
3000/3021 [============================>.] - ETA: 0s - loss: 9.2159 - mse: 9.2159
3021/3021 [==============================] - 1s 173us/sample - loss: 9.2144 - mse: 9.2144 - val_loss: 9.2572 - val_mse: 9.2572
Epoch 73/100
200/3021 [>.............................] - ETA: 0s - loss: 8.8443 - mse: 8.8443
3000/3021 [============================>.] - ETA: 0s - loss: 8.8923 - mse: 8.8923
3021/3021 [==============================] - 1s 176us/sample - loss: 8.8902 - mse: 8.8902 - val_loss: 8.9936 - val_mse: 8.9936
Epoch 74/100
200/3021 [>.............................] - ETA: 0s - loss: 8.7444 - mse: 8.7444
3000/3021 [============================>.] - ETA: 0s - loss: 8.6123 - mse: 8.6123
3021/3021 [==============================] - 1s 168us/sample - loss: 8.6124 - mse: 8.6124 - val_loss: 8.7370 - val_mse: 8.7370
Epoch 75/100
200/3021 [>.............................] - ETA: 0s - loss: 8.5951 - mse: 8.5951
2800/3021 [==========================>...] - ETA: 0s - loss: 8.4382 - mse: 8.4382
3021/3021 [==============================] - 0s 163us/sample - loss: 8.4082 - mse: 8.4082 - val_loss: 8.4819 - val_mse: 8.4819
Epoch 76/100
200/3021 [>.............................] - ETA: 0s - loss: 8.0806 - mse: 8.0806
3021/3021 [==============================] - 0s 147us/sample - loss: 8.1460 - mse: 8.1460 - val_loss: 8.2377 - val_mse: 8.2377
Epoch 77/100
200/3021 [>.............................] - ETA: 0s - loss: 8.3556 - mse: 8.3556
2600/3021 [========================>.....] - ETA: 0s - loss: 7.9297 - mse: 7.9297
3021/3021 [==============================] - 1s 167us/sample - loss: 7.9012 - mse: 7.9012 - val_loss: 7.9929 - val_mse: 7.9929
Epoch 78/100
200/3021 [>.............................] - ETA: 0s - loss: 7.8978 - mse: 7.8978
3021/3021 [==============================] - 0s 152us/sample - loss: 7.6151 - mse: 7.6151 - val_loss: 7.7530 - val_mse: 7.7530
Epoch 79/100
200/3021 [>.............................] - ETA: 0s - loss: 7.6347 - mse: 7.6347
3021/3021 [==============================] - 0s 154us/sample - loss: 7.4149 - mse: 7.4149 - val_loss: 7.5191 - val_mse: 7.5191
Epoch 80/100
200/3021 [>.............................] - ETA: 0s - loss: 7.3151 - mse: 7.3151
3021/3021 [==============================] - 0s 154us/sample - loss: 7.1934 - mse: 7.1934 - val_loss: 7.2922 - val_mse: 7.2922
Epoch 81/100
200/3021 [>.............................] - ETA: 0s - loss: 6.9279 - mse: 6.9279
3021/3021 [==============================] - 0s 141us/sample - loss: 6.9860 - mse: 6.9860 - val_loss: 7.0703 - val_mse: 7.0703
Epoch 82/100
200/3021 [>.............................] - ETA: 0s - loss: 7.0555 - mse: 7.0555
3021/3021 [==============================] - 0s 143us/sample - loss: 6.8599 - mse: 6.8599 - val_loss: 6.8523 - val_mse: 6.8523
Epoch 83/100
200/3021 [>.............................] - ETA: 0s - loss: 6.5748 - mse: 6.5748
3021/3021 [==============================] - 0s 147us/sample - loss: 6.5501 - mse: 6.5501 - val_loss: 6.6392 - val_mse: 6.6392
Epoch 84/100
200/3021 [>.............................] - ETA: 0s - loss: 6.6482 - mse: 6.6482
3021/3021 [==============================] - 0s 143us/sample - loss: 6.3392 - mse: 6.3392 - val_loss: 6.4326 - val_mse: 6.4326
Epoch 85/100
200/3021 [>.............................] - ETA: 0s - loss: 6.5139 - mse: 6.5139
3000/3021 [============================>.] - ETA: 0s - loss: 6.1643 - mse: 6.1643
3021/3021 [==============================] - 0s 141us/sample - loss: 6.1650 - mse: 6.1650 - val_loss: 6.2283 - val_mse: 6.2283
Epoch 86/100
200/3021 [>.............................] - ETA: 0s - loss: 6.0353 - mse: 6.0353
3021/3021 [==============================] - 0s 144us/sample - loss: 5.9635 - mse: 5.9635 - val_loss: 6.0295 - val_mse: 6.0295
Epoch 87/100
200/3021 [>.............................] - ETA: 0s - loss: 6.1347 - mse: 6.1347
2600/3021 [========================>.....] - ETA: 0s - loss: 5.8265 - mse: 5.8265
3021/3021 [==============================] - 0s 148us/sample - loss: 5.8149 - mse: 5.8149 - val_loss: 5.8369 - val_mse: 5.8369
Epoch 88/100
200/3021 [>.............................] - ETA: 0s - loss: 5.8854 - mse: 5.8854
3000/3021 [============================>.] - ETA: 0s - loss: 5.5908 - mse: 5.5908
3021/3021 [==============================] - 0s 164us/sample - loss: 5.5868 - mse: 5.5868 - val_loss: 5.6478 - val_mse: 5.6478
Epoch 89/100
200/3021 [>.............................] - ETA: 0s - loss: 5.3086 - mse: 5.3086
3021/3021 [==============================] - 0s 143us/sample - loss: 5.3936 - mse: 5.3936 - val_loss: 5.4628 - val_mse: 5.4628
Epoch 90/100
200/3021 [>.............................] - ETA: 0s - loss: 5.4477 - mse: 5.4477
2600/3021 [========================>.....] - ETA: 0s - loss: 5.3150 - mse: 5.3150
3021/3021 [==============================] - 0s 147us/sample - loss: 5.2844 - mse: 5.2844 - val_loss: 5.2830 - val_mse: 5.2830
Epoch 91/100
200/3021 [>.............................] - ETA: 0s - loss: 5.2250 - mse: 5.2250
3021/3021 [==============================] - 0s 141us/sample - loss: 4.9997 - mse: 4.9997 - val_loss: 5.1071 - val_mse: 5.1071
Epoch 92/100
200/3021 [>.............................] - ETA: 0s - loss: 4.9942 - mse: 4.9942
3021/3021 [==============================] - 0s 148us/sample - loss: 4.9337 - mse: 4.9337 - val_loss: 4.9379 - val_mse: 4.9379
Epoch 93/100
200/3021 [>.............................] - ETA: 0s - loss: 4.8503 - mse: 4.8503
3021/3021 [==============================] - 0s 137us/sample - loss: 4.6877 - mse: 4.6877 - val_loss: 4.7713 - val_mse: 4.7713
Epoch 94/100
200/3021 [>.............................] - ETA: 0s - loss: 4.5814 - mse: 4.5814
3021/3021 [==============================] - 0s 138us/sample - loss: 4.6023 - mse: 4.6023 - val_loss: 4.6084 - val_mse: 4.6084
Epoch 95/100
200/3021 [>.............................] - ETA: 0s - loss: 4.5169 - mse: 4.5169
2400/3021 [======================>.......] - ETA: 0s - loss: 4.4282 - mse: 4.4282
3021/3021 [==============================] - 0s 155us/sample - loss: 4.4313 - mse: 4.4313 - val_loss: 4.4504 - val_mse: 4.4504
Epoch 96/100
200/3021 [>.............................] - ETA: 0s - loss: 4.4567 - mse: 4.4567
3021/3021 [==============================] - 0s 148us/sample - loss: 4.2736 - mse: 4.2736 - val_loss: 4.2966 - val_mse: 4.2966
Epoch 97/100
200/3021 [>.............................] - ETA: 0s - loss: 4.2702 - mse: 4.2702
3000/3021 [============================>.] - ETA: 0s - loss: 4.0835 - mse: 4.0835
3021/3021 [==============================] - 0s 148us/sample - loss: 4.0805 - mse: 4.0805 - val_loss: 4.1455 - val_mse: 4.1455
Epoch 98/100
200/3021 [>.............................] - ETA: 0s - loss: 4.0149 - mse: 4.0149
3021/3021 [==============================] - 0s 149us/sample - loss: 3.9446 - mse: 3.9446 - val_loss: 3.9998 - val_mse: 3.9998
Epoch 99/100
200/3021 [>.............................] - ETA: 0s - loss: 3.8728 - mse: 3.8728
3000/3021 [============================>.] - ETA: 0s - loss: 3.8000 - mse: 3.8000
3021/3021 [==============================] - 0s 146us/sample - loss: 3.8030 - mse: 3.8030 - val_loss: 3.8586 - val_mse: 3.8586
Epoch 100/100
200/3021 [>.............................] - ETA: 0s - loss: 3.5652 - mse: 3.5652
3021/3021 [==============================] - 0s 141us/sample - loss: 3.6529 - mse: 3.6529 - val_loss: 3.7218 - val_mse: 3.7218Error occurred resetting tf graph: AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'
Run completed: runs/2020-05-04T01-16-22ZBest neural network model best parameters: nodes1 = 392, nodes2 = 392, batch_size = 500, activation1 = tanh, activation2 = sigmoid, learning_rate = 0.0001, epochs = 30, dropout1 = 0.2, dropout2 = 0.5
index = which.max(runs$metric_val_mse)
view_run(runs$run_dir[index])argument 'compressed' is ignored for the internal methodincomplete final line found on 'C:\Users\John\AppData\Local\Temp\RtmpWOAWpS\file17f83e9ee4c/source/FinalProject.R'Neural network models with full train/test RMSE = 4.913784
model = keras_model_sequential()
model %>%
layer_dense(units=64, activation="tanh", input_shape=dim(efw_train)[2]) %>%
layer_dropout(0.05) %>%
layer_dense(units=1)
model %>% compile(
optimizer = optimizer_adam(lr=0.0001),
loss = 'mse',
metrics = c('mse')
)
history <- model %>% fit(
as.matrix(efw_train), trainLabel,
nodes1 = 64,
nodes2 = 64,
batch_size=200,
activation1 = "tanh",
activation2 = "tanh",
epochs=30,
dropout1 = 0.05,
dropout2 = 0.1,
learning_rate=0.0001,
validation_data=list(as.matrix(efw_test), testLabel)
)Train on 3355 samples, validate on 371 samples
Epoch 1/30
200/3355 [>.............................] - ETA: 4s - loss: 42.6679 - mse: 42.6679
3355/3355 [==============================] - 1s 246us/sample - loss: 43.2026 - mse: 43.2026 - val_loss: 43.5009 - val_mse: 43.5009
Epoch 2/30
200/3355 [>.............................] - ETA: 0s - loss: 42.8249 - mse: 42.8249
3000/3355 [=========================>....] - ETA: 0s - loss: 42.3814 - mse: 42.3814
3355/3355 [==============================] - 0s 137us/sample - loss: 42.4340 - mse: 42.4340 - val_loss: 42.8052 - val_mse: 42.8052
Epoch 3/30
200/3355 [>.............................] - ETA: 0s - loss: 42.0398 - mse: 42.0398
3355/3355 [==============================] - 0s 141us/sample - loss: 41.7326 - mse: 41.7326 - val_loss: 42.1448 - val_mse: 42.1448
Epoch 4/30
200/3355 [>.............................] - ETA: 0s - loss: 41.4438 - mse: 41.4438
3200/3355 [===========================>..] - ETA: 0s - loss: 41.2078 - mse: 41.2078
3355/3355 [==============================] - 1s 159us/sample - loss: 41.1679 - mse: 41.1679 - val_loss: 41.4934 - val_mse: 41.4934
Epoch 5/30
200/3355 [>.............................] - ETA: 0s - loss: 40.5872 - mse: 40.5872
3355/3355 [==============================] - 0s 129us/sample - loss: 40.5424 - mse: 40.5424 - val_loss: 40.8832 - val_mse: 40.8832
Epoch 6/30
200/3355 [>.............................] - ETA: 0s - loss: 39.6510 - mse: 39.6510
3355/3355 [==============================] - 0s 129us/sample - loss: 39.9811 - mse: 39.9811 - val_loss: 40.2455 - val_mse: 40.2455
Epoch 7/30
200/3355 [>.............................] - ETA: 0s - loss: 39.4170 - mse: 39.4170
3355/3355 [==============================] - 0s 143us/sample - loss: 39.4008 - mse: 39.4008 - val_loss: 39.6231 - val_mse: 39.6231
Epoch 8/30
200/3355 [>.............................] - ETA: 0s - loss: 38.9923 - mse: 38.9923
3355/3355 [==============================] - 0s 120us/sample - loss: 38.8224 - mse: 38.8224 - val_loss: 38.9904 - val_mse: 38.9904
Epoch 9/30
200/3355 [>.............................] - ETA: 0s - loss: 37.7439 - mse: 37.7439
3200/3355 [===========================>..] - ETA: 0s - loss: 38.2579 - mse: 38.2579
3355/3355 [==============================] - 0s 136us/sample - loss: 38.2543 - mse: 38.2543 - val_loss: 38.3638 - val_mse: 38.3638
Epoch 10/30
200/3355 [>.............................] - ETA: 0s - loss: 37.5983 - mse: 37.5983
3355/3355 [==============================] - 0s 130us/sample - loss: 37.6984 - mse: 37.6984 - val_loss: 37.7169 - val_mse: 37.7169
Epoch 11/30
200/3355 [>.............................] - ETA: 0s - loss: 36.9419 - mse: 36.9419
3200/3355 [===========================>..] - ETA: 0s - loss: 37.1137 - mse: 37.1137
3355/3355 [==============================] - 0s 124us/sample - loss: 37.0887 - mse: 37.0887 - val_loss: 37.0812 - val_mse: 37.0812
Epoch 12/30
200/3355 [>.............................] - ETA: 0s - loss: 35.9521 - mse: 35.9521
3200/3355 [===========================>..] - ETA: 0s - loss: 36.5511 - mse: 36.5511
3355/3355 [==============================] - 0s 137us/sample - loss: 36.5143 - mse: 36.5143 - val_loss: 36.4552 - val_mse: 36.4552
Epoch 13/30
200/3355 [>.............................] - ETA: 0s - loss: 36.5597 - mse: 36.5597
3200/3355 [===========================>..] - ETA: 0s - loss: 35.9333 - mse: 35.9333
3355/3355 [==============================] - 0s 138us/sample - loss: 35.8935 - mse: 35.8935 - val_loss: 35.8040 - val_mse: 35.8040
Epoch 14/30
200/3355 [>.............................] - ETA: 0s - loss: 35.3982 - mse: 35.3982
3355/3355 [==============================] - 1s 154us/sample - loss: 35.3486 - mse: 35.3486 - val_loss: 35.1540 - val_mse: 35.1540
Epoch 15/30
200/3355 [>.............................] - ETA: 0s - loss: 35.0819 - mse: 35.0819
2000/3355 [================>.............] - ETA: 0s - loss: 34.8740 - mse: 34.8740
3355/3355 [==============================] - 1s 150us/sample - loss: 34.7078 - mse: 34.7078 - val_loss: 34.4899 - val_mse: 34.4899
Epoch 16/30
200/3355 [>.............................] - ETA: 0s - loss: 34.2222 - mse: 34.2222
3355/3355 [==============================] - 0s 145us/sample - loss: 34.0387 - mse: 34.0387 - val_loss: 33.8441 - val_mse: 33.8441
Epoch 17/30
200/3355 [>.............................] - ETA: 0s - loss: 33.9236 - mse: 33.9236
2800/3355 [========================>.....] - ETA: 0s - loss: 33.4585 - mse: 33.4585
3355/3355 [==============================] - 0s 142us/sample - loss: 33.4636 - mse: 33.4636 - val_loss: 33.1792 - val_mse: 33.1792
Epoch 18/30
200/3355 [>.............................] - ETA: 0s - loss: 33.0979 - mse: 33.0979
3355/3355 [==============================] - 0s 139us/sample - loss: 32.8302 - mse: 32.8302 - val_loss: 32.5009 - val_mse: 32.5009
Epoch 19/30
200/3355 [>.............................] - ETA: 0s - loss: 31.9113 - mse: 31.9113
2800/3355 [========================>.....] - ETA: 0s - loss: 32.1424 - mse: 32.1424
3355/3355 [==============================] - 0s 142us/sample - loss: 32.1366 - mse: 32.1366 - val_loss: 31.8159 - val_mse: 31.8159
Epoch 20/30
200/3355 [>.............................] - ETA: 0s - loss: 31.4856 - mse: 31.4856
3200/3355 [===========================>..] - ETA: 0s - loss: 31.4798 - mse: 31.4798
3355/3355 [==============================] - 0s 145us/sample - loss: 31.4532 - mse: 31.4532 - val_loss: 31.1256 - val_mse: 31.1256
Epoch 21/30
200/3355 [>.............................] - ETA: 0s - loss: 31.0287 - mse: 31.0287
2600/3355 [======================>.......] - ETA: 0s - loss: 30.9372 - mse: 30.9372
3355/3355 [==============================] - 0s 144us/sample - loss: 30.8251 - mse: 30.8251 - val_loss: 30.4418 - val_mse: 30.4418
Epoch 22/30
200/3355 [>.............................] - ETA: 0s - loss: 31.1461 - mse: 31.1461
2600/3355 [======================>.......] - ETA: 0s - loss: 30.2436 - mse: 30.2436
3355/3355 [==============================] - 0s 125us/sample - loss: 30.1287 - mse: 30.1287 - val_loss: 29.7747 - val_mse: 29.7747
Epoch 23/30
200/3355 [>.............................] - ETA: 0s - loss: 29.6294 - mse: 29.6294
3355/3355 [==============================] - 0s 129us/sample - loss: 29.4585 - mse: 29.4585 - val_loss: 29.0673 - val_mse: 29.0673
Epoch 24/30
200/3355 [>.............................] - ETA: 0s - loss: 28.7965 - mse: 28.7965
3355/3355 [==============================] - 0s 137us/sample - loss: 28.7231 - mse: 28.7231 - val_loss: 28.3693 - val_mse: 28.3693
Epoch 25/30
200/3355 [>.............................] - ETA: 0s - loss: 28.1450 - mse: 28.1450
3355/3355 [==============================] - 0s 142us/sample - loss: 28.0524 - mse: 28.0524 - val_loss: 27.6747 - val_mse: 27.6747
Epoch 26/30
200/3355 [>.............................] - ETA: 0s - loss: 27.5063 - mse: 27.5063
2400/3355 [====================>.........] - ETA: 0s - loss: 27.4054 - mse: 27.4054
3355/3355 [==============================] - 0s 140us/sample - loss: 27.3666 - mse: 27.3666 - val_loss: 26.9622 - val_mse: 26.9622
Epoch 27/30
200/3355 [>.............................] - ETA: 0s - loss: 26.1399 - mse: 26.1399
3355/3355 [==============================] - 0s 131us/sample - loss: 26.6649 - mse: 26.6649 - val_loss: 26.2562 - val_mse: 26.2562
Epoch 28/30
200/3355 [>.............................] - ETA: 0s - loss: 25.8167 - mse: 25.8167
3355/3355 [==============================] - 0s 129us/sample - loss: 25.9378 - mse: 25.9378 - val_loss: 25.5754 - val_mse: 25.5754
Epoch 29/30
200/3355 [>.............................] - ETA: 0s - loss: 25.9502 - mse: 25.9502
3355/3355 [==============================] - 0s 143us/sample - loss: 25.2240 - mse: 25.2240 - val_loss: 24.8550 - val_mse: 24.8550
Epoch 30/30
200/3355 [>.............................] - ETA: 0s - loss: 25.2384 - mse: 25.2384
3355/3355 [==============================] - 0s 133us/sample - loss: 24.5348 - mse: 24.5348 - val_loss: 24.1453 - val_mse: 24.1453predictions = model %>% predict(as.matrix(efw_test))
rmse = function(x, y) {
return((mean((x - y)^2))^0.5)
}
rmse(predictions, testLabel)[1] 4.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